TY - JOUR A1 - Vollmer, Andreas A1 - Nagler, Simon A1 - Hörner, Marius A1 - Hartmann, Stefan A1 - Brands, Roman C. A1 - Breitenbücher, Niko A1 - Straub, Anton A1 - Kübler, Alexander A1 - Vollmer, Michael A1 - Gubik, Sebastian A1 - Lang, Gernot A1 - Wollborn, Jakob A1 - Saravi, Babak T1 - Performance of artificial intelligence-based algorithms to predict prolonged length of stay after head and neck cancer surgery JF - Heliyon N2 - Background Medical resource management can be improved by assessing the likelihood of prolonged length of stay (LOS) for head and neck cancer surgery patients. The objective of this study was to develop predictive models that could be used to determine whether a patient's LOS after cancer surgery falls within the normal range of the cohort. Methods We conducted a retrospective analysis of a dataset consisting of 300 consecutive patients who underwent head and neck cancer surgery between 2017 and 2022 at a single university medical center. Prolonged LOS was defined as LOS exceeding the 75th percentile of the cohort. Feature importance analysis was performed to evaluate the most important predictors for prolonged LOS. We then constructed 7 machine learning and deep learning algorithms for the prediction modeling of prolonged LOS. Results The algorithms reached accuracy values of 75.40 (radial basis function neural network) to 97.92 (Random Trees) for the training set and 64.90 (multilayer perceptron neural network) to 84.14 (Random Trees) for the testing set. The leading parameters predicting prolonged LOS were operation time, ischemia time, the graft used, the ASA score, the intensive care stay, and the pathological stages. The results revealed that patients who had a higher number of harvested lymph nodes (LN) had a lower probability of recurrence but also a greater LOS. However, patients with prolonged LOS were also at greater risk of recurrence, particularly when fewer (LN) were extracted. Further, LOS was more strongly correlated with the overall number of extracted lymph nodes than with the number of positive lymph nodes or the ratio of positive to overall extracted lymph nodes, indicating that particularly unnecessary lymph node extraction might be associated with prolonged LOS. Conclusions The results emphasize the need for a closer follow-up of patients who experience prolonged LOS. Prospective trials are warranted to validate the present results. KW - prediction KW - head and neck cancer KW - machine learning KW - deep learning KW - artificial intelligence KW - length of stay KW - cancer Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-350416 SN - 2405-8440 VL - 9 IS - 11 ER - TY - JOUR A1 - Vollmer, Andreas A1 - Vollmer, Michael A1 - Lang, Gernot A1 - Straub, Anton A1 - Kübler, Alexander A1 - Gubik, Sebastian A1 - Brands, Roman C. A1 - Hartmann, Stefan A1 - Saravi, Babak T1 - Performance analysis of supervised machine learning algorithms for automatized radiographical classification of maxillary third molar impaction JF - Applied Sciences N2 - Background: Oro-antral communication (OAC) is a common complication following the extraction of upper molar teeth. The Archer and the Root Sinus (RS) systems can be used to classify impacted teeth in panoramic radiographs. The Archer classes B-D and the Root Sinus classes III, IV have been associated with an increased risk of OAC following tooth extraction in the upper molar region. In our previous study, we found that panoramic radiographs are not reliable for predicting OAC. This study aimed to (1) determine the feasibility of automating the classification (Archer/RS classes) of impacted teeth from panoramic radiographs, (2) determine the distribution of OAC stratified by classification system classes for the purposes of decision tree construction, and (3) determine the feasibility of automating the prediction of OAC utilizing the mentioned classification systems. Methods: We utilized multiple supervised pre-trained machine learning models (VGG16, ResNet50, Inceptionv3, EfficientNet, MobileNetV2), one custom-made convolutional neural network (CNN) model, and a Bag of Visual Words (BoVW) technique to evaluate the performance to predict the clinical classification systems RS and Archer from panoramic radiographs (Aim 1). We then used Chi-square Automatic Interaction Detectors (CHAID) to determine the distribution of OAC stratified by the Archer/RS classes to introduce a decision tree for simple use in clinics (Aim 2). Lastly, we tested the ability of a multilayer perceptron artificial neural network (MLP) and a radial basis function neural network (RBNN) to predict OAC based on the high-risk classes RS III, IV, and Archer B-D (Aim 3). Results: We achieved accuracies of up to 0.771 for EfficientNet and MobileNetV2 when examining the Archer classification. For the AUC, we obtained values of up to 0.902 for our custom-made CNN. In comparison, the detection of the RS classification achieved accuracies of up to 0.792 for the BoVW and an AUC of up to 0.716 for our custom-made CNN. Overall, the Archer classification was detected more reliably than the RS classification when considering all algorithms. CHAID predicted 77.4% correctness for the Archer classification and 81.4% for the RS classification. MLP (AUC: 0.590) and RBNN (AUC: 0.590) for the Archer classification as well as MLP 0.638) and RBNN (0.630) for the RS classification did not show sufficient predictive capability for OAC. Conclusions: The results reveal that impacted teeth can be classified using panoramic radiographs (best AUC: 0.902), and the classification systems can be stratified according to their relationship to OAC (81.4% correct for RS classification). However, the Archer and RS classes did not achieve satisfactory AUCs for predicting OAC (best AUC: 0.638). Additional research is needed to validate the results externally and to develop a reliable risk stratification tool based on the present findings. KW - oro-antral communication KW - oro-antral fistula KW - prediction KW - machine learning KW - teeth extraction KW - complications KW - classification KW - artificial intelligence Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-281662 SN - 2076-3417 VL - 12 IS - 13 ER - TY - JOUR A1 - Latoschik, Marc Erich A1 - Wienrich, Carolin T1 - Congruence and plausibility, not presence: pivotal conditions for XR experiences and effects, a novel approach JF - Frontiers in Virtual Reality N2 - Presence is often considered the most important quale describing the subjective feeling of being in a computer-generated and/or computer-mediated virtual environment. The identification and separation of orthogonal presence components, i.e., the place illusion and the plausibility illusion, has been an accepted theoretical model describing Virtual Reality (VR) experiences for some time. This perspective article challenges this presence-oriented VR theory. First, we argue that a place illusion cannot be the major construct to describe the much wider scope of virtual, augmented, and mixed reality (VR, AR, MR: or XR for short). Second, we argue that there is no plausibility illusion but merely plausibility, and we derive the place illusion caused by the congruent and plausible generation of spatial cues and similarly for all the current model’s so-defined illusions. Finally, we propose congruence and plausibility to become the central essential conditions in a novel theoretical model describing XR experiences and effects. KW - XR KW - experience KW - presence KW - congruence KW - plausibility KW - coherence KW - theory KW - prediction Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-284787 SN - 2673-4192 VL - 3 ER - TY - JOUR A1 - Vollmer, Andreas A1 - Vollmer, Michael A1 - Lang, Gernot A1 - Straub, Anton A1 - Shavlokhova, Veronika A1 - Kübler, Alexander A1 - Gubik, Sebastian A1 - Brands, Roman A1 - Hartmann, Stefan A1 - Saravi, Babak T1 - Associations between periodontitis and COPD: An artificial intelligence-based analysis of NHANES III JF - Journal of Clinical Medicine N2 - A number of cross-sectional epidemiological studies suggest that poor oral health is associated with respiratory diseases. However, the number of cases within the studies was limited, and the studies had different measurement conditions. By analyzing data from the National Health and Nutrition Examination Survey III (NHANES III), this study aimed to investigate possible associations between chronic obstructive pulmonary disease (COPD) and periodontitis in the general population. COPD was diagnosed in cases where FEV (1)/FVC ratio was below 70% (non-COPD versus COPD; binary classification task). We used unsupervised learning utilizing k-means clustering to identify clusters in the data. COPD classes were predicted with logistic regression, a random forest classifier, a stochastic gradient descent (SGD) classifier, k-nearest neighbors, a decision tree classifier, Gaussian naive Bayes (GaussianNB), support vector machines (SVM), a custom-made convolutional neural network (CNN), a multilayer perceptron artificial neural network (MLP), and a radial basis function neural network (RBNN) in Python. We calculated the accuracy of the prediction and the area under the curve (AUC). The most important predictors were determined using feature importance analysis. Results: Overall, 15,868 participants and 19 feature variables were included. Based on k-means clustering, the data were separated into two clusters that identified two risk characteristic groups of patients. The algorithms reached AUCs between 0.608 (DTC) and 0.953% (CNN) for the classification of COPD classes. Feature importance analysis of deep learning algorithms indicated that age and mean attachment loss were the most important features in predicting COPD. Conclusions: Data analysis of a large population showed that machine learning and deep learning algorithms could predict COPD cases based on demographics and oral health feature variables. This study indicates that periodontitis might be an important predictor of COPD. Further prospective studies examining the association between periodontitis and COPD are warranted to validate the present results. KW - COPD KW - periodontitis KW - bone loss KW - machine learning KW - prediction KW - artificial intelligence KW - model KW - gingivitis Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-312713 SN - 2077-0383 VL - 11 IS - 23 ER - TY - JOUR A1 - Hartrampf, Philipp E. A1 - Seitz, Anna Katharina A1 - Weinzierl, Franz-Xaver A1 - Serfling, Sebastian E. A1 - Schirbel, Andreas A1 - Rowe, Steven P. A1 - Kübler, Hubert A1 - Buck, Andreas K. A1 - Werner, Rudolf A. T1 - Baseline clinical characteristics predict overall survival in patients undergoing radioligand therapy with [\(^{177}\)Lu]Lu-PSMA I&T during long-term follow-up JF - European Journal of Nuclear Medicine and Molecular Imaging N2 - Background Radioligand therapy (RLT) with \(^{177}\)Lu-labeled prostate-specific membrane antigen (PSMA) ligands is associated with prolonged overall survival (OS) in patients with advanced, metastatic castration-resistant prostate cancer (mCRPC). A substantial number of patients, however, are prone to treatment failure. We aimed to determine clinical baseline characteristics to predict OS in patients receiving [\(^{177}\)Lu]Lu-PSMA I&T RLT in a long-term follow-up. Materials and methods Ninety-two mCRPC patients treated with [\(^{177}\)Lu]Lu-PSMA I&T with a follow-up of at least 18 months were retrospectively identified. Multivariable Cox regression analyses were performed for various baseline characteristics, including laboratory values, Gleason score, age, prior therapies, and time interval between initial diagnosis and first treatment cycle (interval\(_{Diagnosis-RLT}\), per 12 months). Cutoff values for significant predictors were determined using receiver operating characteristic (ROC) analysis. ROC-derived thresholds were then applied to Kaplan–Meier analyses. Results Baseline C-reactive protein (CRP; hazard ratio [HR], 1.10, 95% CI 1.02–1.18; P = 0.01), lactate dehydrogenase (LDH; HR, 1.07, 95% CI 1.01–1.11; P = 0.01), aspartate aminotransferase (AST; HR, 1.16, 95% CI 1.06–1.26; P = 0.001), and interval\(_{Diagnosis-RLT}\) (HR, 0.95, 95% CI 0.91–0.99; P = 0.02) were identified as independent prognostic factors for OS. The following respective ROC-based thresholds were determined: CRP, 0.98 mg/dl (area under the curve [AUC], 0.80); LDH, 276.5 U/l (AUC, 0.83); AST, 26.95 U/l (AUC, 0.73); and interval\(_{Diagnosis-RLT}\), 43.5 months (AUC, 0.68; P < 0.01, respectively). Respective Kaplan–Meier analyses demonstrated a significantly longer median OS of patients with lower CRP, lower LDH, and lower AST, as well as prolonged interval\(_{Diagnosis-RLT}\) (P ≤ 0.01, respectively). Conclusion In mCRPC patients treated with [\(^{177}\)Lu]Lu-PSMA I&T, baseline CRP, LDH, AST, and time interval until RLT initiation (thereby reflecting a possible indicator for tumor aggressiveness) are independently associated with survival. Our findings are in line with previous findings on [\(^{177}\)Lu]Lu-PSMA-617, and we believe that these clinical baseline characteristics may support the nuclear medicine specialist to identify long-term survivors. KW - PSMA KW - prostate cancer KW - [177Lu]Lu-PSMA I&T KW - radioligand therapy KW - overall survival KW - prediction Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-324573 VL - 49 IS - 12 ER - TY - JOUR A1 - Wischnewsky, Manfred A1 - Schwentner, Lukas A1 - Diessner, Joachim A1 - De Gregorio, Amelie A1 - Joukhadar, Ralf A1 - Davut, Dayan A1 - Salmen, Jessica A1 - Bekes, Inga A1 - Kiesel, Matthias A1 - Müller-Reiter, Max A1 - Blettner, Maria A1 - Wolters, Regine A1 - Janni, Wolfgang A1 - Kreienberg, Rolf A1 - Wöckel, Achim A1 - Ebner, Florian T1 - BRENDA-Score, a hghly significant, internally and externally validated prognostic marker for metastatic recurrence: analysis of 10,449 primary breast cancer patients JF - Cancers N2 - Background Current research in breast cancer focuses on individualization of local and systemic therapies with adequate escalation or de-escalation strategies. As a result, about two-thirds of breast cancer patients can be cured, but up to one-third eventually develop metastatic disease, which is considered incurable with currently available treatment options. This underscores the importance to develop a metastatic recurrence score to escalate or de-escalate treatment strategies. Patients and methods Data from 10,499 patients were available from 17 clinical cancer registries (BRENDA-project. In total, 8566 were used to develop the BRENDA-Index. This index was calculated from the regression coefficients of a Cox regression model for metastasis-free survival (MFS). Based on this index, patients were categorized into very high, high, intermediate, low, and very low risk groups forming the BRENDA-Score. Bootstrapping was used for internal validation and an independent dataset of 1883 patients for external validation. The predictive accuracy was checked by Harrell's c-index. In addition, the BRENDA-Score was analyzed as a marker for overall survival (OS) and compared to the Nottingham prognostic score (NPS). Results: Intrinsic subtypes, tumour size, grading, and nodal status were identified as statistically significant prognostic factors in the multivariate analysis. The five prognostic groups of the BRENDA-Score showed highly significant (p < 0.001) differences regarding MFS:low risk: hazard ratio (HR) = 2.4, 95%CI (1.7–3.3); intermediate risk: HR = 5.0, 95%CI.(3.6–6.9); high risk: HR = 10.3, 95%CI (7.4–14.3) and very high risk: HR = 18.1, 95%CI (13.2–24.9). The external validation showed congruent results. A multivariate Cox regression model for OS with BRENDA-Score and NPS as covariates showed that of these two scores only the BRENDA-Score is significant (BRENDA-Score p < 0.001; NPS p = 0.447). Therefore, the BRENDA-Score is also a good prognostic marker for OS. Conclusion: The BRENDA-Score is an internally and externally validated robust predictive tool for metastatic recurrence in breast cancer patients. It is based on routine parameters easily accessible in daily clinical care. In addition, the BRENDA-Score is a good prognostic marker for overall survival. Highlights: The BRENDA-Score is a highly significant predictive tool for metastatic recurrence of breast cancer patients. The BRENDA-Score is stable for at least the first five years after primary diagnosis, i.e., the sensitivities and specificities of this predicting system is rather similar to the NPI with AUCs between 0.76 and 0.81 the BRENDA-Score is a good prognostic marker for overall survival. KW - breast cancer KW - risk KW - prediction KW - BRENDA KW - score KW - follow up Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-241064 SN - 2072-6694 VL - 13 IS - 13 ER - TY - JOUR A1 - Bäuerlein, Carina A. A1 - Qureischi, Musga A1 - Mokhtari, Zeinab A1 - Tabares, Paula A1 - Brede, Christian A1 - Jordán Garrote, Ana-Laura A1 - Riedel, Simone S. A1 - Chopra, Martin A1 - Reu, Simone A1 - Mottok, Anja A1 - Arellano-Viera, Estibaliz A1 - Graf, Carolin A1 - Kurzwart, Miriam A1 - Schmiedgen, Katharina A1 - Einsele, Hermann A1 - Wölfl, Matthias A1 - Schlegel, Paul-Gerhardt A1 - Beilhack, Andreas T1 - A T-Cell Surface Marker Panel Predicts Murine Acute Graft-Versus-Host Disease JF - Frontiers in Immunology N2 - Acute graft-versus-host disease (aGvHD) is a severe and often life-threatening complication of allogeneic hematopoietic cell transplantation (allo-HCT). AGvHD is mediated by alloreactive donor T-cells targeting predominantly the gastrointestinal tract, liver, and skin. Recent work in mice and patients undergoing allo-HCT showed that alloreactive T-cells can be identified by the expression of α4β7 integrin on T-cells even before manifestation of an aGvHD. Here, we investigated whether the detection of a combination of the expression of T-cell surface markers on peripheral blood (PB) CD8\(^+\) T-cells would improve the ability to predict aGvHD. To this end, we employed two independent preclinical models of minor histocompatibility antigen mismatched allo-HCT following myeloablative conditioning. Expression profiles of integrins, selectins, chemokine receptors, and activation markers of PB donor T-cells were measured with multiparameter flow cytometry at multiple time points before the onset of clinical aGvHD symptoms. In both allo-HCT models, we demonstrated a significant upregulation of α4β7 integrin, CD162E, CD162P, and conversely, a downregulation of CD62L on donor T-cells, which could be correlated with the development of aGvHD. Other surface markers, such as CD25, CD69, and CC-chemokine receptors were not found to be predictive markers. Based on these preclinical data from mouse models, we propose a surface marker panel on peripheral blood T-cells after allo-HCT combining α4β7 integrin with CD62L, CD162E, and CD162P (cutaneous lymphocyte antigens, CLA, in humans) to identify patients at risk for developing aGvHD early after allo-HCT. KW - acute graft-versus-host disease KW - alloreactive T cells KW - transplantation KW - prediction KW - mouse models Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-224290 SN - 1664-3224 VL - 11 ER - TY - JOUR A1 - Davidson, Padraig A1 - Düking, Peter A1 - Zinner, Christoph A1 - Sperlich, Billy A1 - Hotho, Andreas T1 - Smartwatch-Derived Data and Machine Learning Algorithms Estimate Classes of Ratings of Perceived Exertion in Runners: A Pilot Study JF - Sensors N2 - The rating of perceived exertion (RPE) is a subjective load marker and may assist in individualizing training prescription, particularly by adjusting running intensity. Unfortunately, RPE has shortcomings (e.g., underreporting) and cannot be monitored continuously and automatically throughout a training sessions. In this pilot study, we aimed to predict two classes of RPE (≤15 “Somewhat hard to hard” on Borg’s 6–20 scale vs. RPE >15 in runners by analyzing data recorded by a commercially-available smartwatch with machine learning algorithms. Twelve trained and untrained runners performed long-continuous runs at a constant self-selected pace to volitional exhaustion. Untrained runners reported their RPE each kilometer, whereas trained runners reported every five kilometers. The kinetics of heart rate, step cadence, and running velocity were recorded continuously ( 1 Hz ) with a commercially-available smartwatch (Polar V800). We trained different machine learning algorithms to estimate the two classes of RPE based on the time series sensor data derived from the smartwatch. Predictions were analyzed in different settings: accuracy overall and per runner type; i.e., accuracy for trained and untrained runners independently. We achieved top accuracies of 84.8 % for the whole dataset, 81.8 % for the trained runners, and 86.1 % for the untrained runners. We predict two classes of RPE with high accuracy using machine learning and smartwatch data. This approach might aid in individualizing training prescriptions. KW - artificial intelligence KW - endurance KW - exercise intensity KW - precision training KW - prediction KW - wearable Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-205686 SN - 1424-8220 VL - 20 IS - 9 ER - TY - JOUR A1 - Meier, Sandra M. A1 - Kähler, Anna K. A1 - Bergen, Sarah E. A1 - Sullivan, Patrick F. A1 - Hultman, Christina M. A1 - Mattheisen, Manuel T1 - Chronicity and Sex Affect Genetic Risk Prediction in Schizophrenia JF - Frontiers in Psychiatry N2 - Schizophrenia (SCZ) is a severe mental disorder with immense personal and societal costs; identifying individuals at risk is therefore of utmost importance. Genomic risk profile scores (GRPS) have been shown to significantly predict cases-control status. Making use of a large-population based sample from Sweden, we replicate a previous finding demonstrating that the GRPS is strongly associated with admission frequency and chronicity of SCZ. Furthermore, we were able to show a substantial gap in prediction accuracy between males and females. In sum, our results indicate that prediction accuracy by GRPS depends on clinical and demographic characteristics. KW - schizophrenia KW - polygenic risk score KW - prediction KW - sex KW - course Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-205677 SN - 1664-0640 VL - 11 ER - TY - JOUR A1 - Heß, Verena A1 - Meng, Karin A1 - Schulte, Thomas A1 - Neuderth, Silke A1 - Bengel, Jürgen A1 - Faller, Hermann A1 - Schuler, Michael T1 - Prevalence and predictors of cancer patients' unexpressed needs in the admission interview of inpatient rehabilitation JF - Psycho‐Oncology N2 - Objective The admission interview in oncological inpatient rehabilitation might be a good opportunity to identify cancer patients' needs present after acute treatment. However, a relevant number of patients may not express their needs. In this study, we examined (a) the proportion of cancer patients with unexpressed needs, (b) topics of unexpressed needs and reasons for not expressing needs, (c) correlations of not expressing needs with several patient characteristics, and (d) predictors of not expressing needs. Methods We enrolled 449 patients with breast, prostate, and colon cancer at beginning and end of inpatient rehabilitation. We obtained self‐reports about unexpressed needs and health‐related variables (quality of life, depression, anxiety, adjustment disorder, and health literacy). We estimated frequencies and conducted correlation and ordinal logistic regression analyses. Results A quarter of patients stated they had “rather not” or “not at all” expressed all relevant needs. Patients mostly omitted fear of cancer recurrence. Most frequent reasons for not expressing needs were being focused on physical consequences of cancer, concerns emerging only later, and not knowing about the possibility of talking about distress. Not expressing needs was associated with several health‐related outcomes, for example, emotional functioning, adjustment disorder, fear of progression, and health literacy. Depression measured at the beginning of rehabilitation showed only small correlations and is therefore not sufficient to identify patients with unexpressed needs. Conclusions A relevant proportion of cancer patients reported unexpressed needs in the admission interview. This was associated with decreased mental health. Therefore, it seems necessary to support patients in expressing needs. KW - cancer KW - inpatient rehabilitation KW - oncology KW - prediction KW - prevalence KW - unexpressed needs Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-228369 VL - 29 IS - 10 SP - 1549 EP - 1556 ER - TY - JOUR A1 - Kingslake, Jonathan A1 - Dias, Rebecca A1 - Dawson, Gerard R. A1 - Simon, Judit A1 - Goodwin, Guy M. A1 - Harmer, Catherine J. A1 - Morriss, Richard A1 - Brown, Susan A1 - Guo, Boliang A1 - Dourish, Colin T. A1 - Ruhé, Henricus G. A1 - Lever, Anne G. A1 - Veltman, Dick J. A1 - van Schaik, Anneke A1 - Deckert, Jürgen A1 - Reif, Andreas A1 - Stäblein, Michael A1 - Menke, Andreas A1 - Gorwood, Philip A1 - Voegeli, Géraldine A1 - Perez, Victor A1 - Browning, Michael T1 - The effects of using the PReDicT Test to guide the antidepressant treatment of depressed patients: study protocol for a randomised controlled trial JF - Trials N2 - Background Antidepressant medication is commonly used to treat depression. However, many patients do not respond to the first medication prescribed and improvements in symptoms are generally only detectable by clinicians 4–6 weeks after the medication has been initiated. As a result, there is often a long delay between the decision to initiate an antidepressant medication and the identification of an effective treatment regimen. Previous work has demonstrated that antidepressant medications alter subtle measures of affective cognition in depressed patients, such as the appraisal of facial expression. Furthermore, these cognitive effects of antidepressants are apparent early in the course of treatment and can also predict later clinical response. This trial will assess whether an electronic test of affective cognition and symptoms (the Predicting Response to Depression Treatment Test; PReDicT Test) can be used to guide antidepressant treatment in depressed patients and, therefore, hasten treatment response compared to a control group of patients treated as usual. Methods/design The study is a randomised, two-arm, multi-centre, open-label, clinical investigation of a medical device, the PReDicT Test. It will be conducted in five European countries (UK, France, Spain, Germany and the Netherlands) in depressed patients who are commencing antidepressant medication. Patients will be randomised to treatment guided by the PReDicT Test (PReDicT arm) or to Treatment as Usual (TaU arm). Patients in the TaU arm will be treated as per current standard guidelines in their particular country. Patients in the PReDicT arm will complete the PReDicT Test after 1 (and if necessary, 2) weeks of treatment. If the test indicates non-response to the treatment, physicians will be advised to immediately alter the patient’s antidepressant therapy by dose escalation or switching to another compound. The primary outcome of the study is the proportion of patients showing a clinical response (defined as 50% or greater decrease in baseline scores of depressionmeasured using the Quick Inventory of Depressive Symptoms – Self-Rated questionnaire) at week 8. Health economic and acceptability data will also be collected and analysed. Discussion This trial will test the clinical efficacy, cost-effectiveness and acceptability of using the novel PReDicT Test to guide antidepressant treatment selection in depressed patients. Trial registration ClinicalTrials.gov, ID: NCT02790970. Registered on 30 March 2016. KW - psychiatry KW - depression KW - prediction KW - treatment KW - antidepressant KW - primary care Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-173012 VL - 18 ER - TY - JOUR A1 - Rowinska, Zuzanna A1 - Gorressen, Simone A1 - Merx, Marc W. A1 - Koeppel, Thomas A. A1 - Liehn, Elisa A. A1 - Zernecke, Alma T1 - Establishment of a New Murine Elastase-Induced Aneurysm Model Combined with Transplantation JF - PLOS ONE N2 - Introduction: The aim of our study was to develop a reproducible murine model of elastase-induced aneurysm formation combined with aortic transplantation. Methods: Adult male mice (n = 6-9 per group) underwent infrarenal, orthotopic transplantation of the aorta treated with elastase or left untreated. Subsequently, both groups of mice were monitored by ultrasound until 7 weeks after grafting. Results: Mice receiving an elastase-pretreated aorta developed aneurysms and exhibited a significantly increased diastolic vessel diameter compared to control grafted mice at 7 week after surgery (1.11 +/- 0.10 mm vs. 0.75 +/- 0.03 mm; p <= 0.001). Histopathological examination revealed disruption of medial elastin, an increase in collagen content and smooth muscle cells, and neointima formation in aneurysm grafts. Conclusions: We developed a reproducible murine model of elastase-induced aneurysm combined with aortic transplantation. This model may be suitable to investigate aneurysm-specific inflammatory processes and for use in gene-targeted animals. KW - abdominal aortic-aneurysm KW - mouse models KW - prediction KW - dilation KW - rupture Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-115774 SN - 1932-6203 VL - 9 IS - 7 ER - TY - JOUR A1 - Kincaid, Rodney P. A1 - Chen, Yating A1 - Cox, Jennifer E. A1 - Rethwilm, Axel A1 - Sullivan, Christopher S. T1 - Noncanonical MicroRNA (miRNA) Biogenesis Gives Rise to Retroviral Mimics of Lymphoproliferative and Immunosuppressive Host miRNAs JF - mBio N2 - MicroRNAs (miRNAs) play regulatory roles in diverse processes in both eukaryotic hosts and their viruses, yet fundamental questions remain about which viruses code for miRNAs and the functions that they serve. Simian foamy viruses (SFVs) of Old World monkeys and apes can zoonotically infect humans and, by ill-defined mechanisms, take up lifelong infections in their hosts. Here, we report that SFVs encode multiple miRNAs via a noncanonical mode of biogenesis. The primary SFV miRNA transcripts (pri-miRNAs) are transcribed by RNA polymerase III (RNAP III) and take multiple forms, including some that are cleaved by Drosha. However, these miRNAs are generated in a context-dependent fashion, as longer RNAP II transcripts spanning this region are resistant to Drosha cleavage. This suggests that the virus may avoid any fitness penalty that could be associated with viral genome/transcript cleavage. Two SFV miRNAs share sequence similarity and functionality with notable host miRNAs, the lymphoproliferative miRNA miR-155 and the innate immunity suppressor miR-132. These results have important implications regarding foamy virus biology, viral miRNAs, and the development of retroviral-based vectors. IMPORTANCE Fundamental questions remain about which viruses encode miRNAs and their associated functions. Currently, few natural viruses with RNA genomes have been reported to encode miRNAs. Simian foamy viruses are retroviruses that are prevalent in nonhuman host populations, and some can zoonotically infect humans who hunt primates or work as animal caretakers. We identify a cluster of miRNAs encoded by SFV. Characterization of these miRNAs reveals evolutionarily conserved, unconventional mechanisms to generate small RNAs. Several SFV miRNAs share sequence similarity and functionality with host miRNAs, including the oncogenic miRNA miR-155 and innate immunity suppressor miR-132. Strikingly, unrelated herpesviruses also tap into one or both of these same regulatory pathways, implying relevance to a broad range of viruses. These findings provide new insights with respect to foamy virus biology and vectorology. KW - MIR-155 KW - simian foamy viruses KW - long terminal repeat KW - viral microRNAs KW - RNA KW - infection KW - herpesvirus KW - recognition KW - prediction KW - ortholog Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-117216 SN - 2150-7511 VL - 5 IS - 2 ER - TY - JOUR A1 - Samimi, C. A1 - Fink, A. H. A1 - Paeth, H. T1 - The 2007 flood in the Sahel: causes, characteristics and its presentation in the media and FEWS NET JF - Natural Hazards and Earth System Sciences N2 - During the rainy season in 2007, reports about exceptional rains and floodings in the Sahel were published in the media, especially in August and September. Institutions and organizations like the World Food Programme (WFP) and FEWS NET put the events on the agenda and released alerts and requested help. The partly controversial picture was that most of the Sahel faced a crisis caused by widespread floodings. Our study shows that the rainy season in 2007 was exceptional with regard to rainfall amount and return periods. In many areas the event had a return period between 1 and 50 yr with high spatial heterogeneity, with the exception of the Upper Volta basin, which yielded return periods of up to 1200 yr. Despite the strong rainfall, the interpretation of satellite images show that the floods were mainly confined to lakes and river beds. However, the study also proves the difficulties in assessing the meteorological processes and the demarcation of flooded areas in satellite images without ground truthing. These facts and the somewhat vague and controversial reports in the media and FEWS NET demonstrate that it is crucial to thoroughly analyze such events at a regional and local scale involving the local population. KW - prediction KW - satellite rainfall products KW - tropical North-Africa KW - West-Africa KW - climate change KW - summer rainfall KW - variability KW - SST KW - teleconnection KW - validation Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-131790 VL - 12 IS - 2 SP - 313 EP - 325 ER -