TY - JOUR A1 - Wieber, Markus A1 - Lang, Stefan A1 - Rohse, Stefan A1 - Habersack, Ralph A1 - Burschka, Christian T1 - Synthese und Kristallstruktur von Triphenyltelluroniumsulfid T1 - Synthesis and Crystal Structure of Triphenyltelluroniumsulfide N2 - No abstract available KW - Chemie KW - Triphenyltelluroniumsulfide KW - Synthesis KW - NMR Data KW - Crystal Structure KW - Secondary Bonding Y1 - 1994 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-47151 ER - TY - JOUR A1 - Pachel, Christina A1 - Mathes, Denise A1 - Bayer, Barbara A1 - Dienesch, Charlotte A1 - Wangorsch, Gaby A1 - Heitzmann, Wolfram A1 - Lang, Isabell A1 - Ardehali, Hossein A1 - Ertl, Georg A1 - Dandekar, Thomas A1 - Wajant, Harald A1 - Frantz, Stefan T1 - Exogenous Administration of a Recombinant Variant of TWEAK Impairs Healing after Myocardial Infarction by Aggravation of Inflammation JF - PLoS ONE N2 - Background: Tumor necrosis factor-like weak inducer of apoptosis (TWEAK) and its receptor fibroblast growth factorinducible 14 (Fn14) are upregulated after myocardial infarction (MI) in both humans and mice. They modulate inflammation and the extracellular matrix, and could therefore be important for healing and remodeling after MI. However, the function of TWEAK after MI remains poorly defined. Methods and results: Following ligation of the left coronary artery, mice were injected twice per week with a recombinant human serum albumin conjugated variant of TWEAK (HSA-Flag-TWEAK), mimicking the activity of soluble TWEAK. Treatment with HSA-Flag-TWEAK resulted in significantly increased mortality in comparison to the placebo group due to myocardial rupture. Infarct size, extracellular matrix remodeling, and apoptosis rates were not different after MI. However, HSA-Flag-TWEAK treatment increased infiltration of proinflammatory cells into the myocardium. Accordingly, depletion of neutrophils prevented cardiac ruptures without modulating all-cause mortality. Conclusion: Treatment of mice with HSA-Flag-TWEAK induces myocardial healing defects after experimental MI. This is mediated by an exaggerated neutrophil infiltration into the myocardium. KW - apoptosis KW - myocardial infarction KW - neutrophils KW - cytokines KW - inflammation KW - myocardium KW - heart KW - extracellular matrix Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-129889 VL - 8 IS - 11 ER - TY - THES A1 - Lang, Stefan T1 - Transportuntersuchungen an vertikal- und lateral-gekoppelten niederdimensionalen Elektronensystemen T1 - Transport Investigations on Vertically and Laterally Coupled Low Dimensional Electron-Systems N2 - An Y-Schaltern konnte eine nichtlineare Verschiebung der Schwellspannung beobachtet werden. In einem Y-Schalter spaltet sich ein Stammwellenleiter über einen Verzweigungspunkt Y-förmig in zwei Astwellenleiter auf, so dass prinzipiell mehrere Maxima im Leitungsband existieren. Daher wurde ein Modell entwickelt, das die Dynamik der Leitungsbandmaxima im elektrischen Feld beschreibt. Dieses beinhaltet sowohl die geometrischen Kapazitäten als auch die Quantenkapazitäten des Y-Schalters. Zudem konnte gezeigt werden, dass lokalisierte Ladungen zur Beschreibung des Schaltens notwendig sind. Die Verschiebung der Schwellspannungen kann hierbei sehr gut durch das Zusammenspiel der klassischen und der Quantenkapazitäten beschrieben werden, wobei sich herausstellt, dass die Quantenkapazitäten des Systems einen dominierenden Einfluss auf das Schaltverhalten nehmen. Für X-förmige Verzweigungen wird gezeigt, dass für ausgewählte Spannungsbereiche an den vier lateralen Kontrollgates der Transport durch den X-Schalter entweder geblockt oder erlaubt ist. Dies wurde auf die Ausbildung eines Quantenpunkts im Zentrum des X-Schalters zurückgeführt. Es liegt also Coulomb-Blockade vor und der Elektronentransport durch die Struktur kann mittels eines Stabilitätsdiagramms analysiert werden. Es zeigt sich, dass die zentrale Elektroneninsel einen Durchmesser von etwa 20nm hat und eine Ladeenergie von E_C=15meV besitzt. Weiterhin konnten Transportbereiche aufgezeigt werden, welche einen negativen differentiellen Leitwert basierend auf einer dynamischen Kapazität aufweisen. Außerdem konnte in größeren Verzweigungen bistabiles Schalten aufgrund von Selbstschalten nachgewiesen werden. Es ist hierbei sowohl invertierendes als auch nicht-invertierendes Schalten zu beobachten. Es wurden Quantendrahttransistoren auf der Basis von wenigen Nanometer übereinander liegenden, vertikal gekoppelten Elektronengasen realisiert. Die Herstellung der Strukturen stellt hierbei besondere Herausforderungen an die Prozessierungstechniken. So mussten Barrieren unterschiedlicher Al-Konzentrationen während des Wachstums mittels Molekularstrahlepitaxie eingebracht werden, um einen Al-selektiven Ätzprozess anwenden zu können. Die beiden Elektronengase sind nach dem Wachstum lediglich durch eine 7nm dicke AlGaAs-Barriere voneinander getrennt. Um die beiden Elektronengase getrennt voneinander zu kontaktieren war es anschließend notwendig, ein spezielles Ätzverfahren anzuwenden. Es zeigte sich, dass eines der 2DEGs aufgrund des extrem geringen Abstands als hocheffektives Gate für das andere 2DEG dienen kann, wobei für die untersuchten Strukturen eine Gateeffektivität nahe eins, das heißt ein ideales Schalten, beschrieben wird. In Strukturen geringerer Dotierkonzentration wird anschließend hocheffektives Schalten bis zu einer Temperatur von 250K demonstriert. Basierend auf derartigen vertikal gekoppelten Elektronengasen wurden außerdem trocken geätzte Y-Transistoren hergestellt. Es kann bistabiles Schalten nachgewiesen werden, wobei analog zu den X-Strukturen ein Ast als Gate dient. Die Hysterese des bistabilen Schaltens kann dabei so klein eingestellt werden, dass rauschaktiviertes Schalten zwischen den beiden Ausgangszuständen des Systems zu beobachten ist. Es zeigt sich, dass das Schalten in solchen Strukturen mit einer Aktivierungsenergie von lediglich 0.4 kT erfolgt. Somit ist dieser Wert kleiner als das thermische Limit für stabiles Schalten in klassischen Bauelementen. Der 2-Terminal-Leitwert eines Quantendrahts bei Magnetfeldumkehr zeigt Asymmetrien, welche stark sowohl von den Spannungen an den Gates abhängen. Der Strom durch den Quantendraht kann einerseits mittels eines lateralen Gates und außerdem durch ein auf der Oberfläche liegendes vertikales Metallgate gesteuert werden. Hierbei wurde der Kanal einerseits durch Verarmung des 2DEGs über ein Metallgate definiert. Andererseits wurde auf der gegenüberliegenden Seite eine Potentialbarriere durch den Ätzgraben aufgebaut. Es stellte sich heraus, dass die gemessenen Asymmetrien auf den Wechsel zwischen elastischer Streuung der Kanalelektronen an der elektrostatischen Begrenzung und inelastischer Streuung an der geätzten Grenzfläche zurückzuführen sind. Für hohe Vorwärtsspannungen zeigt sich, dass der asymmetrische Anteil der dominierende Term im Leitwert ist. Dies erlaubt es, die vorliegende Struktur als Magnetfeldsensor, mit einer Sensitivität von 3.4mVT zu verwenden. Als Ausblick für die Zukunft kann festgestellt werden, dass komplex geformte Leiterbahnen durch die Ausnutzung von Effekten wie Coulomb-Blockade und Selbstschalten ein großes Potential für zukünftige Schaltkreise besitzen. Da Schaltenergien durch das Ausnutzen von Systemrauschen kleiner als das thermische Limit auftreten soll es ein Ziel für die Zukunft sein, Neuron ähnliche Schaltkreise auf der Basis von verzweigten Schaltern zu realisieren. N2 - This thesis reports on transport investigations performed with semiconductor nanostructures carrying low-dimensional, highly mobile electron gases. These structures are based on modulation doped GaAs/AlGaAs layers. Lithographic techniques were subsequently applied to define narrow channels with different geometries. In this way, laterally as well as vertically coupled conductors like Y- and X-structures were realized. Non-linear threshold voltage shifts in an electron Y-branch switch We have studied the threshold characteristics and gate efficiencies of electron Y-branch switches controlled by in-plane gates. The threshold voltage was found to shift in a nonlinear manner for a certain regime of inplane electric fields controlled by the voltage difference between the gates along the junction. This result is interpreted in terms of local conduction band maxima in the stem and the branches. To explain the non-linear threshold we propose a model based on coupled quantum capacitances and geometrical capacitances including charges localized in the Y-branch. Also the switching efficiencies, which are measures of how much of a change in the electrochemical potential of the gate is transferred into a change of the conduction band maximum, in the switch depend on the gate voltages. The switching efficiency is larger for those parts of the Y-branch with the smallest quantum capacitance. Network-calculations enabled us to determine the relevant system-parameters. Coulomb-blockade and bistability in X-structures We demonstrated charge transport to be blocked for certain voltage regimes applied to four laterally coupled sidegates of an X-structure. This is related to the formation of an electron island, a quantum dot, in the branching section of the device. Therefore, diamond patterns associated with Coulomb- blockade were observed in transport spectroscopy and the electron transport across the structure was analyzed by means of a stability diagram. It was found that the central electron island has a diameter of about 20nm with a charging energy of E_C=15meV. Furthermore we identified transport regimes showing a negative differential conductance. This was interpreted in terms of a dynamic capacitance between the island and the respective drain contact. Moreover bistable switching was demonstrated as a result of self-gating. Inverting as well as non-inverting switching in the self-gating regime is also realized. Coupled two dimensional electron gases Double GaAs quantum wells embedded between modulation-doped AlGaAs barriers with different Al contents were grown by molecular beam epitaxy. Independent electric contacts to each well were realized by applying different etching techniques. Particularly, the lower quantum well was electrically pinched off by an undercut of the lower AlGaAs barrier exploiting an Al-selective etching process. In contrast, the upper quantum well was locally depleted by top etched trenches. Transistor operation of quantum wires defined in such bilayers is demonstrated at room temperature with one GaAs layer used as conducting channel controlled by the other nearby layer as efficient quantum gate. Furthermore, in devices exploiting a low doping concentration, highly effective gating with gate leverage factors near unity is realized up to T=250K. Finally, bistable switching operation is observed for structures exploiting a floating gate. Provided this floating gate becomes charged, it is demonstrated that the threshold voltage of the waveguide increases drastically. Magnetic-field induced asymmetries in quantum wires with asymmetric gate coupling The two-terminal conductance of GaAs/AlGaAs quantum wires was studied in the non-linear regime. The quantum wires were coupled asymmetrically to a metal gate and investigated for a magnetic field perpendicular to the sample surface. A sidegate was defined by wet chemical etching of a deep trench. Adjacent to this trench a narrow metal top gate was deposited on the sample's surface. Therefore, the channel was on the one hand defined by local depletion of the 2DEG by means of a negative topgate voltage. On the other hand, the etched trench leads to a potential barrier serving also as sidewall. It was found that the conductance of the quantum wire shows pronounced asymmetries when the magnetic field is reversed. These asymmetries are related to different scattering mechanisms, i.e. specular scattering of the channel electrons at the sidewall caused by an electrostatic confinement and backscattering at the boundary due to the etched trench. The asymmetric conductance was identified to increase significantly with the bias voltage. This probably allows the application of such structures as magnetic field sensors with a sensitivity of 3.4mV/T KW - Quantendraht KW - Quantenwell KW - Transistor KW - Mesoskopischer Transport KW - Quantumwire KW - Electronics KW - Transistor Y1 - 2009 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-37652 ER - TY - JOUR A1 - Chopra, Martin A1 - Lang, Isabell A1 - Salzmann, Steffen A1 - Pachel, Christina A1 - Kraus, Sabrina A1 - Bäuerlein, Carina A. A1 - Brede, Christian A1 - Jordán Garrote, Ana-Laura A1 - Mattenheimer, Katharina A1 - Ritz, Miriam A1 - Schwinn, Stefanie A1 - Graf, Carolin A1 - Schäfer, Viktoria A1 - Frantz, Stefan A1 - Einsele, Hermann A1 - Wajant, Harald A1 - Beilhack, Andreas T1 - Tumor Necrosis Factor Induces Tumor Promoting and Anti-Tumoral Effects on Pancreatic Cancer via TNFR1 JF - PLoS ONE N2 - Multiple activities are ascribed to the cytokine tumor necrosis factor (TNF) in health and disease. In particular, TNF was shown to affect carcinogenesis in multiple ways. This cytokine acts via the activation of two cell surface receptors, TNFR1, which is associated with inflammation, and TNFR2, which was shown to cause anti-inflammatory signaling. We assessed the effects of TNF and its two receptors on the progression of pancreatic cancer by in vivo bioluminescence imaging in a syngeneic orthotopic tumor mouse model with Panc02 cells. Mice deficient for TNFR1 were unable to spontaneously reject Panc02 tumors and furthermore displayed enhanced tumor progression. In contrast, a fraction of wild type (37.5%), TNF deficient (12.5%), and TNFR2 deficient mice (22.2%) were able to fully reject the tumor within two weeks. Pancreatic tumors in TNFR1 deficient mice displayed increased vascular density, enhanced infiltration of CD4+ T cells and CD4+ forkhead box P3 (FoxP3)+ regulatory T cells (Treg) but reduced numbers of CD8+ T cells. These alterations were further accompanied by transcriptional upregulation of IL4. Thus, TNF and TNFR1 are required in pancreatic ductal carcinoma to ensure optimal CD8+ T cell-mediated immunosurveillance and tumor rejection. Exogenous systemic administration of human TNF, however, which only interacts with murine TNFR1, accelerated tumor progression. This suggests that TNFR1 has basically the capability in the Panc02 model to trigger pro-and anti-tumoral effects but the spatiotemporal availability of TNF seems to determine finally the overall outcome. KW - Bioluminescence KW - cancer treatment KW - cell staining KW - cytokines KW - immune cells KW - metastasis KW - regulatory T cells KW - T cells Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-97246 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 - Chifu, Irina A1 - Heinze, Britta A1 - Fuss, Carmina T. A1 - Lang, Katharina A1 - Kroiss, Matthias A1 - Kircher, Stefan A1 - Ronchi, Cristina L. A1 - Altieri, Barbara A1 - Schirbel, Andreas A1 - Fassnacht, Martin A1 - Hahner, Stefanie T1 - Impact of the Chemokine Receptors CXCR4 and CXCR7 on Clinical Outcome in Adrenocortical Carcinoma JF - Frontiers in Endocrinology N2 - Chemokine receptors have a negative impact on tumor progression in several human cancers and have therefore been of interest for molecular imaging and targeted therapy. However, their clinical and prognostic significance in adrenocortical carcinoma (ACC) is unknown. The aim of this study was to evaluate the chemokine receptor profile in ACC and to analyse its association with clinicopathological characteristics and clinical outcome. A chemokine receptor profile was initially evaluated by quantitative PCR in 4 normal adrenals, 18 ACC samples and human ACC cell line NCI-H295. High expression of CXCR4 and CXCR7 in both healthy and malignant adrenal tissue and ACC cells was confirmed. In the next step, we analyzed the expression and cellular localization of CXCR4 and CXCR7 in ACC by immunohistochemistry in 187 and 84 samples, respectively. These results were correlated with clinicopathological parameters and survival outcome. We detected strong membrane expression of CXCR4 and CXCR7 in 50% of ACC samples. Strong cytoplasmic CXCR4 staining was more frequent among samples derived from metastases compared to primaries (p=0.01) and local recurrences (p=0.04). CXCR4 membrane staining positively correlated with proliferation index Ki67 (r=0.17, p=0.028). CXCR7 membrane staining negatively correlated with Ki67 (r=−0.254, p=0.03) but positively with tumor size (r=0.3, p=0.02). No differences in progression-free or overall survival were observed between patients with strong and weak staining intensities for CXCR4 or CXCR7. Taken together, high expression of CXCR4 and CXCR7 in both local tumors and metastases suggests that some ACC patients might benefit from CXCR4/CXCR7-targeted therapy. KW - chemokine receptor KW - prognosis KW - adrenocortical carcinoma KW - CXCR4 KW - CXCR7 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-216494 SN - 1664-2392 VL - 11 ER - TY - JOUR A1 - Vollmer, Andreas A1 - Saravi, Babak A1 - Vollmer, Michael A1 - Lang, Gernot Michael A1 - Straub, Anton A1 - Brands, Roman C. A1 - Kübler, Alexander A1 - Gubik, Sebastian A1 - Hartmann, Stefan T1 - Artificial intelligence-based prediction of oroantral communication after tooth extraction utilizing preoperative panoramic radiography JF - Diagnostics N2 - Oroantral communication (OAC) is a common complication after tooth extraction of upper molars. Profound preoperative panoramic radiography analysis might potentially help predict OAC following tooth extraction. In this exploratory study, we evaluated n = 300 consecutive cases (100 OAC and 200 controls) and trained five machine learning algorithms (VGG16, InceptionV3, MobileNetV2, EfficientNet, and ResNet50) to predict OAC versus non-OAC (binary classification task) from the input images. Further, four oral and maxillofacial experts evaluated the respective panoramic radiography and determined performance metrics (accuracy, area under the curve (AUC), precision, recall, F1-score, and receiver operating characteristics curve) of all diagnostic approaches. Cohen's kappa was used to evaluate the agreement between expert evaluations. The deep learning algorithms reached high specificity (highest specificity 100% for InceptionV3) but low sensitivity (highest sensitivity 42.86% for MobileNetV2). The AUCs from VGG16, InceptionV3, MobileNetV2, EfficientNet, and ResNet50 were 0.53, 0.60, 0.67, 0.51, and 0.56, respectively. Expert 1–4 reached an AUC of 0.550, 0.629, 0.500, and 0.579, respectively. The specificity of the expert evaluations ranged from 51.74% to 95.02%, whereas sensitivity ranged from 14.14% to 59.60%. Cohen's kappa revealed a poor agreement for the oral and maxillofacial expert evaluations (Cohen's kappa: 0.1285). Overall, present data indicate that OAC cannot be sufficiently predicted from preoperative panoramic radiography. The false-negative rate, i.e., the rate of positive cases (OAC) missed by the deep learning algorithms, ranged from 57.14% to 95.24%. Surgeons should not solely rely on panoramic radiography when evaluating the probability of OAC occurrence. Clinical testing of OAC is warranted after each upper-molar tooth extraction. KW - artificial intelligence KW - deep learning KW - X-ray KW - tooth extraction KW - oroantral fistula KW - operative planning Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-278814 SN - 2075-4418 VL - 12 IS - 6 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 - Lang, Stefan J. A1 - Messmer, Elisabeth M. A1 - Geerling, Gerd A1 - Mackert, Marc J. A1 - Brunner, Tobias A1 - Dollak, Sylvia A1 - Kutchoukov, Borislav A1 - Böhringer, Daniel A1 - Reinhard, Thomas A1 - Maier, Philip T1 - Prospective, randomized, double-blind trial to investigate the efficacy and safety of corneal cross-linking to halt the progression of keratoconus JF - BMC Ophthalmology N2 - Background: Corneal cross-linking is widely used to treat keratoconus. However, to date, only limited data from randomized trials support its efficacy. Methods: The efficacy and safety of corneal cross-linking for halting progression of keratoconus were investigated in a prospective, randomized, blinded, placebo controlled, multicentre trial. Twenty-nine keratoconus patients were randomized in three trial centres. The mean age at inclusion was 28 years. Longitudinal changes in corneal refraction were assessed by linear regression. The best corrected visual acuity, surface defects and corneal inflammation were also assessed. These data were analysed with a multifactorial linear regression model. Results: A total of 15 eyes were randomized to the treatment and 14 to the control group. Follow-up averaged 1098 days. Corneal refractive power decreased on average (+/-standard deviation) by 0.35 +/- 0.58 dioptres/year in the treatment group. The controls showed an increase of 0.11 +/- 0.61 dioptres/year. This difference was statistically significant (p = 0.02). Conclusions: Our data suggest that corneal cross-linking is an effective treatment for some patients to halt the progression of keratoconus. However, some of the treated patients still progressed, whereas some untreated controls improved. Therefore, further investigations are necessary to decide which patients require treatment and which do not. KW - ultraviolet-a KW - riboflavin KW - Scheimpflug KW - eyes KW - haze Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-151498 VL - 15 IS - 78 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 - Automated assessment of radiographic bone loss in the posterior maxilla utilizing a multi-object detection artificial intelligence algorithm JF - Applied Sciences N2 - 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. KW - radiographic bone loss KW - alveolar bone loss KW - maxillofacial surgery KW - deep learning KW - classification KW - artificial intelligence KW - object detection Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-305050 SN - 2076-3417 VL - 13 IS - 3 ER - 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 -