Final Report on the German Clinical Reference Corpus 3000PA.

We here report on one of the outcomes of a large-scale German research program, the Medical Informatics Initiative (MII), aiming at the development of a solid data and software infrastructure for German-language clinical natural language processing. Within this framework, we have developed 3000PA, a national clinical reference corpus composed of patient records from three clinical university sites and annotated with a multitude of semantic annotation layers (including medical named entities, semantic and temporal relations between entities, as well as certainty and negation information related to entities and relations). This non-sharable corpus has been complemented by three sharable ones (JSYNCC, GGPONC, and GRASCCO). Overall, 3000PA, JSYNCC and GRASCCO feature about 2.1 million metadata points.

GRASCCO - The First Publicly Shareable, Multiply-Alienated German Clinical Text Corpus.

We describe the creation of GRASCCO, a novel German-language corpus composed of some 60 clinical documents with more than.43,000 tokens. GRASCCO is a synthetic corpus resulting from a series of alienation steps to obfuscate privacy-sensitive information contained in real clinical documents, the true origin of all GRASCCO texts. Therefore, it is publicly shareable without any legal restrictions We also explore whether this corpus still represents common clinical language use by comparison with a real (non-shareable) clinical corpus we developed as a contribution to the Medical Informatics Initiative in Germany (MII) within the SMITH consortium. We find evidence that such a claim can indeed be made.

Piloting the Update: The Use of Therapeutic Relationship for Change - A Free Energy Account.

We apply the Free Energy Principle (FEP) to cognitive behavioral therapy (CBT). FEP describes the basic functioning of the brain as a predictive organ and states that any self-organizing system that is in equilibrium with its environment must minimize its free energy. Based on an internal model of the world and the self, predictions-so-called priors-are created, which are matched with the information input. The sum of prediction errors corresponds to the Free Energy, which must be minimized. Internal models can be identified with the cognitive-affective schemas of the individual that has become dysfunctional in patients. The role of CBT in this picture is to help the patient update her/his priors. They have evolved in learning history and no longer provide adaptive predictions. We discuss the process of updating in terms of the exploration-exploitation dilemma. This consists of the extent to which one relies on what one already has, i.e., whether one continues to maintain and "exploit" one's previous priors ("better safe than sorry") or whether one does explore new data that lead to an update of priors. Questioning previous priors triggers stress, which is associated with increases in Free Energy in short term. The role of therapeutic relationship is to buffer this increase in Free Energy, thereby increasing the level of perceived safety. The therapeutic relationship is represented in a dual model of affective alliance and goal attainment alliance and is aligned with FEP. Both forms of alliance support exploration and updating of priors. All aspects are illustrated with the help of a clinical case example.

Pseudonymization of PHI Items in German Clinical Reports.

We describe the adaptation of a non-clinical pseudonymization system, originally developed for a German email corpus, for clinical use. This tool replaces previously identified Protected Health Information (PHI) items as carriers of privacy-sensitive information (original names for people, organizations, places, etc.) with semantic type-conformant, yet, fictitious surrogates. We evaluate the generated substitutes for grammatical correctness, semantic and medical plausibility and find particularly low numbers of error instances (less than 1%) on all of these dimensions.

Optimized Identification of Advanced Chronic Kidney Disease and Absence of Kidney Disease by Combining Different Electronic Health Data Resources and by Applying Machine Learning Strategies.

Automated identification of advanced chronic kidney disease (CKD ≥ III) and of no known kidney disease (NKD) can support both clinicians and researchers. We hypothesized that identification of CKD and NKD can be improved, by combining information from different electronic health record (EHR) resources, comprising laboratory values, discharge summaries and ICD-10 billing codes, compared to using each component alone. We included EHRs from 785 elderly multimorbid patients, hospitalized between 2010 and 2015, that were divided into a training and a test (n = 156) dataset. We used both the area under the receiver operating characteristic (AUROC) and under the precision-recall curve (AUCPR) with a 95% confidence interval for evaluation of different classification models. In the test dataset, the combination of EHR components as a simple classifier identified CKD ≥ III (AUROC 0.96[0.93-0.98]) and NKD (AUROC 0.94[0.91-0.97]) better than laboratory values (AUROC CKD 0.85[0.79-0.90], NKD 0.91[0.87-0.94]), discharge summaries (AUROC CKD 0.87[0.82-0.92], NKD 0.84[0.79-0.89]) or ICD-10 billing codes (AUROC CKD 0.85[0.80-0.91], NKD 0.77[0.72-0.83]) alone. Logistic regression and machine learning models improved recognition of CKD ≥ III compared to the simple classifier if only laboratory values were used (AUROC 0.96[0.92-0.99] vs. 0.86[0.81-0.91], p < 0.05) and improved recognition of NKD if information from previous hospital stays was used (AUROC 0.99[0.98-1.00] vs. 0.95[0.92-0.97]], p < 0.05). Depending on the availability of data, correct automated identification of CKD ≥ III and NKD from EHRs can be improved by generating classification models based on the combination of different EHR components.

An Evolutionary Approach to the Annotation of Discharge Summaries.

We here describe the evolution of annotation guidelines for major clinical named entities, namely Diagnosis, Findings and Symptoms, on a corpus of approximately 1,000 German discharge letters. Due to their intrinsic opaqueness and complexity, clinical annotation tasks require continuous guideline tuning, beginning from the initial definition of crucial entities and the subsequent iterative evolution of guidelines based on empirical evidence. We describe rationales for adaptation, with focus on several metrical criteria and task-centered clinical constraints.

Annotating German Clinical Documents for De-Identification.

We devised annotation guidelines for the de-identification of German clinical documents and assembled a corpus of 1,106 discharge summaries and transfer letters with 44K annotated protected health information (PHI) items. After three iteration rounds, our annotation team finally reached an inter-annotator agreement of 0.96 on the instance level and 0.97 on the token level of annotation (averaged pair-wise F1 score). To establish a baseline for automatic de-identification on our corpus, we trained a recurrent neural network (RNN) and achieved F1 scores greater than 0.9 on most major PHI categories.

3000PA-Towards a National Reference Corpus of German Clinical Language.

We introduce 3000PA, a clinical document corpus composed of 3,000 EPRs from three different clinical sites, which will serve as the backbone of a national reference language resource for German clinical NLP. We outline its design principles, results from a medication annotation campaign and the evaluation of a first medication information extraction prototype using a subset of 3000PA.

Embodied Cognition and the Direct Induction of Affect as a Compliment to Cognitive Behavioural Therapy.

We make the case for the possible integration of affect experience induced via embodiment techniques with CBT for the treatment of emotional disorders in clinical settings. Theoretically we propose a possible integration of cognitive behavioural theory, neuroscience, embodied cognition and important processes of client change outcomes such as the therapeutic alliance to enhance client outcomes. We draw from evidence of bidirectional effects between embodiment modes of bottom-up (sensory-motor simulations giving rise to important basis of knowledge) and top-down (abstract mental representations of knowledge) processes such as CBT in psychotherapy. The paper first describes the dominance and success of CBT for the treatment of a wide range of clinical disorders. Some limitations of CBT, particularly for depression are also outlined. There is a growing body of evidence for the added value of experiential affect-focused interventions combined with CBT. Evidence for the embodied model of cognition and emotion is reviewed. Advantages of embodiment is highlighted as a complimentary process model to deepen the intensity and valence of affective experience. It is suggested that an integrated embodiment approach with CBT enhances outcomes across a wide range of emotional disorders. A description of our embodiment method integrated with CBT for inducing affective experience, emotional regulation, acceptance of unwanted emotions and emotional mastery is given. Finally, the paper highlights the importance of the therapeutic alliance as a critical component of the change process. The paper ends with a case study highlighting some clinical strategies that may aid the therapist to integrate embodiment techniques in CBT that can further explore in future research on affective experience in CBT for a wider range of clinical disorders.

CDA-Compliant Section Annotation of German-Language Discharge Summaries: Guideline Development, Annotation Campaign, Section Classification.

We present the outcome of an annotation effort targeting the content-sensitive segmentation of German clinical reports into sections. We recruited an annotation team of up to eight medical students to annotate a clinical text corpus on a sentence-by-sentence basis in four pre-annotation iterations and one final main annotation step. The annotation scheme we came up with adheres to categories developed for clinical documents in the HL7-CDA (Clinical Document Architecture) standard for section headings. Once the scheme became stable, we ran the main annotation campaign on the complete set of roughly 1,000 clinical documents. Due to its reliance on the CDA standard, the annotation scheme allows the integration of legacy and newly produced clinical documents within a common pipeline. We then made direct use of the annotations by training a baseline classifier to automatically identify sections in clinical reports.

Direct observation of proton pumping by a eukaryotic P-type ATPase.

In eukaryotes, P-type adenosine triphosphatases (ATPases) generate the plasma membrane potential and drive secondary transport systems; however, despite their importance, their regulation remains poorly understood. We monitored at the single-molecule level the activity of the prototypic proton-pumping P-type ATPase Arabidopsis thaliana isoform 2 (AHA2). Our measurements, combined with a physical nonequilibrium model of vesicle acidification, revealed that pumping is stochastically interrupted by long-lived (~100 seconds) inactive or leaky states. Allosteric regulation by pH gradients modulated the switch between these states but not the pumping or leakage rates. The autoinhibitory regulatory domain of AHA2 reduced the intrinsic pumping rates but increased the dwell time in the active pumping state. We anticipate that similar functional dynamics underlie the operation and regulation of many other active transporters.

Single vesicle biochips for ultra-miniaturized nanoscale fluidics and single molecule bioscience.

One of the major bottlenecks in the development of biochips is maintaining the structure and function of biomolecules when interfacing them with hard matter (glass, plastics, metals, etc.), a challenge that is exacerbated during miniaturization that inevitably increases the interface to volume ratio of these devices. Biochips based on immobilized vesicles circumvent this problem by encapsulating biomolecules in the protective environment of a lipid bilayer, thus minimizing interactions with hard surfaces. Here we review the development of biochips based on arrays of single nanoscale vesicles, their fabrication via controlled self-assembly, and their characterization using fluorescence microscopy. We also highlight their applications in selected fields such as nanofluidics and single molecule bioscience. Despite their great potential for improved biocompatibility, extreme miniaturization and high throughput, single vesicle biochips are still a niche technology that has yet to establish its commercial relevance.

Functional brain network abnormalities during verbal working memory performance in adolescents and young adults with dyslexia.

Behavioral and functional neuroimaging studies indicate deficits in verbal working memory (WM) and frontoparietal dysfunction in individuals with dyslexia. Additionally, structural brain abnormalities in dyslexics suggest a dysconnectivity of brain regions associated with phonological processing. However, little is known about the functional neuroanatomy underlying cognitive dysfunction in dyslexia. In this study, functional magnetic resonance imaging and multivariate analytic techniques were used to investigate patterns of functional connectivity during a verbal WM task in individuals with dyslexia (n=12) and control subjects (n=13). Dyslexics were not significantly slower than controls; however, they were less accurate with increasing WM demand. Independent component analysis identified 18 independent components (ICs) among which two ICs were selected for further analyses. These ICs included functional networks which were positively correlated with the delay period of the activation task in both healthy controls and dyslexics. Connectivity abnormalities in dyslexics were detected within both networks of interest: within a "phonological" left-lateralized prefrontal network, increased functional connectivity was found in left prefrontal and inferior parietal regions. Within an "executive" bilateral frontoparietal network, dyslexics showed a decreased connectivity pattern comprising bilateral dorsolateral prefrontal and posterior parietal regions, while increased connectivity was found in the left angular gyrus, the left hippocampal cortex and the right thalamus. The functional connectivity strength in the latter regions was associated with WM task accuracy and with the numbers of errors during a spelling test. These data suggest functional connectivity abnormalities in two spatiotemporally dissociable brain networks underlying WM dysfunction in individuals with dyslexia.

Constructing size distributions of liposomes from single-object fluorescence measurements.

We describe in detail a simple technique to construct the size distribution of liposome formulations from single-object fluorescence measurements. Liposomes that are fluorescently labeled in their membrane are first immobilized on a surface at dilute densities and then imaged individually using epi-fluorescence microscopy. The integrated intensities of several thousand single liposomes are collected and evaluated within minutes by automated image processing, using the user-friendly freeware ImageJ. The mean intensity of the liposome population is then calculated and scaled in units of length (nm) by relating the intensity data to the mean diameter obtained from a reference measurement with dynamic light scattering. We explain the process of constructing the size distributions in a step-by-step manner, starting with the preparation of liposomes through the final acquisition of size histograms. Detailed advice is given concerning critical parameters of image acquisition and processing. Size histograms constructed from single-particle measurements provide detailed information on complex distributions that may be easily averaged out in ensemble measurements (e.g., light scattering). In addition, the technique allows accurate measurements of polydisperse samples (e.g., nonextruded liposome preparations).

Neural correlates of working memory performance in adolescents and young adults with dyslexia.

Behavioral studies indicate deficits in phonological working memory (WM) and executive functioning in dyslexics. However, little is known about the underlying functional neuroanatomy. In the present study, neural correlates of WM in adolescents and young adults with dyslexia were investigated using event-related functional magnetic resonance imaging (fMRI) and a parametric verbal WM task which required the manipulation of verbal material. Dyslexics were not significantly slower than controls; however, they were less accurate with the highest WM demand. The functional analysis excluded incorrectly performed and omitted trials, thus controlling for potential activation confounds. Compared with control subjects, both increased and decreased activation of the prefrontal cortex were found in the dyslexic group. Dyslexics showed significantly more activation than controls with increasing WM demand in the left superior frontal gyrus (BA 8), as well as in the inferior frontal gyrus including Broca's area (BA 44) and its right homologue. Less activation was found in the middle frontal gyrus (BA 6) and in the superior parietal cortex (BA 7). A positive correlation between activation of prefrontal regions and verbal WM performance (as measured by digit span backwards) was found only in the dyslexic group. Accuracy deficits at the highest cognitive demand during the verbal WM task and the digit span backwards suggest that manipulation rather than maintenance is selectively impaired in dyslexics. The fMRI data provide further evidence for functional differences in cortical regions associated with language processing and executive function in subjects with dyslexia.