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Die Tagungsreihe ECLE – Economy, Criminal Law, Ethics – steht für die im Einklang mit der Frankfurter Schule des Strafrechts stehende Überzeugung, dass moderne strafrechtliche Fragen, die einen Bezug zur Wirtschaft aufweisen, nicht durch das Recht alleine zu beantworten sind. Vielmehr sind die Perspektiven der Kriminalwissenschaften, der Ökonomie, der Politik und der Ethik mit der Praxis von Wirtschaftsstrafrecht und -strafverfahren zu konfrontieren und im Wege einer fächer- und länderübergreifenden Diskussion anzugehen. In ihrer zehnten Ausgabe stand das Thema „Wirtschaftsstrafrecht und Systeme“ im Mittelpunkt.
Die Tagungsreihe wird von Prof. Dr. Matthias Jahn, Eberhard Kempf, Prof. Dr. Cornelius Prittwitz und Dr. Charlotte Schmitt-Leonardy organisiert.
In pathology, tissue images are evaluated using a light microscope, relying on the expertise and experience of pathologists. There is a great need for computational methods to quantify and standardize histological observations. Computational quantification methods become more and more essential to evaluate tissue images. In particular, the distribution of tumor cells and their microenvironment are of special interest. Here, we systematically investigated tumor cell properties and their spatial neighborhood relations by a new application of statistical analysis to whole slide images of Hodgkin lymphoma, a tumor arising in lymph nodes, and inflammation of lymph nodes called lymphadenitis. We considered properties of more than 400, 000 immunohistochemically stained, CD30-positive cells in 35 whole slide images of tissue sections from subtypes of the classical Hodgkin lymphoma, nodular sclerosis and mixed cellularity, as well as from lymphadenitis. We found that cells of specific morphology exhibited significant favored and unfavored spatial neighborhood relations of cells in dependence of their morphology. This information is important to evaluate differences between Hodgkin lymph nodes infiltrated by tumor cells (Hodgkin lymphoma) and inflamed lymph nodes, concerning the neighborhood relations of cells and the sizes of cells. The quantification of neighborhood relations revealed new insights of relations of CD30-positive cells in different diagnosis cases. The approach is general and can easily be applied to whole slide image analysis of other tumor types.
The first measurement of two-pion Bose–Einstein correlations in central Pb–Pb collisions at √sNN=2.76 TeV at the Large Hadron Collider is presented. We observe a growing trend with energy now not only for the longitudinal and the outward but also for the sideward pion source radius. The pion homogeneity volume and the decoupling time are significantly larger than those measured at RHIC.
Inclusive transverse momentum spectra of primary charged particles in Pb–Pb collisions at √sNN=2.76 TeV have been measured by the ALICE Collaboration at the LHC. The data are presented for central and peripheral collisions, corresponding to 0–5% and 70–80% of the hadronic Pb–Pb cross section. The measured charged particle spectra in |η|<0.8 and 0.3<pT<20 GeV/c are compared to the expectation in pp collisions at the same sNN, scaled by the number of underlying nucleon–nucleon collisions. The comparison is expressed in terms of the nuclear modification factor RAA. The result indicates only weak medium effects (RAA≈0.7) in peripheral collisions. In central collisions, RAA reaches a minimum of about 0.14 at pT=6–7 GeV/c and increases significantly at larger pT. The measured suppression of high-pT particles is stronger than that observed at lower collision energies, indicating that a very dense medium is formed in central Pb–Pb collisions at the LHC.
The inclusive charged particle transverse momentum distribution is measured in proton–proton collisions at s=900 GeV at the LHC using the ALICE detector. The measurement is performed in the central pseudorapidity region (|η|<0.8) over the transverse momentum range 0.15<pT<10 GeV/c. The correlation between transverse momentum and particle multiplicity is also studied. Results are presented for inelastic (INEL) and non-single-diffractive (NSD) events. The average transverse momentum for |η|<0.8 is 〈pT〉INEL=0.483±0.001 (stat.)±0.007 (syst.) GeV/c and 〈pT〉NSD=0.489±0.001 (stat.)±0.007 (syst.) GeV/c, respectively. The data exhibit a slightly larger 〈pT〉 than measurements in wider pseudorapidity intervals. The results are compared to simulations with the Monte Carlo event generators PYTHIA and PHOJET.
Rapidity and transverse momentum dependence of inclusive J/ψ production in pp collisions at √s=7 TeV
(2011)
The ALICE experiment at the LHC has studied inclusive J/ψ production at central and forward rapidities in pp collisions at √s=7 TeV. In this Letter, we report on the first results obtained detecting the J/ψ through the dilepton decay into e+e− and μ+μ− pairs in the rapidity ranges |y|<0.9 and 2.5<y<4, respectively, and with acceptance down to zero pT. In the dielectron channel the analysis was carried out on a data sample corresponding to an integrated luminosity Lint=5.6 nb−1 and the number of signal events is NJ/ψ=352±32(stat.)±28(syst.); the corresponding figures in the dimuon channel are Lint=15.6 nb−1 and NJ/ψ=1924±77(stat.)±144(syst.). The measured production cross sections are σJ/ψ(|y|<0.9)=10.7±1.0(stat.)±1.6(syst.)−2.3+1.6(syst.pol.)μb and σJ/ψ(2.5<y<4)=6.31±0.25(stat.)±0.76(syst.)−1.96+0.95(syst.pol.)μb. The differential cross sections, in transverse momentum and rapidity, of the J/ψ were also measured.
Background: Signal transduction pathways are important cellular processes to maintain the cell’s integrity. Their imbalance can cause severe pathologies. As signal transduction pathways feature complex regulations, they form intertwined networks. Mathematical models aim to capture their regulatory logic and allow an unbiased analysis of robustness and vulnerability of the signaling network. Pathway detection is yet a challenge for the analysis of signaling networks in the field of systems biology. A rigorous mathematical formalism is lacking to identify all possible signal flows in a network model.
Results: In this paper, we introduce the concept of Manatee invariants for the analysis of signal transduction networks. We present an algorithm for the characterization of the combinatorial diversity of signal flows, e.g., from signal reception to cellular response. We demonstrate the concept for a small model of the TNFR1-mediated NF- κB signaling pathway. Manatee invariants reveal all possible signal flows in the network. Further, we show the application of Manatee invariants for in silico knockout experiments. Here, we illustrate the biological relevance of the concept.
Conclusions: The proposed mathematical framework reveals the entire variety of signal flows in models of signaling systems, including cyclic regulations. Thereby, Manatee invariants allow for the analysis of robustness and vulnerability of signaling networks. The application to further analyses such as for in silico knockout was shown. The new framework of Manatee invariants contributes to an advanced examination of signaling systems.
The degradation of cytosol-invading pathogens by autophagy, a process known as xenophagy, is an important mechanism of the innate immune system. Inside the host, Salmonella Typhimurium invades epithelial cells and resides within a specialized intracellular compartment, the Salmonella-containing vacuole. A fraction of these bacteria does not persist inside the vacuole and enters the host cytosol. Salmonella Typhimurium that invades the host cytosol becomes a target of the autophagy machinery for degradation. The xenophagy pathway has recently been discovered, and the exact molecular processes are not entirely characterized. Complete kinetic data for each molecular process is not available, so far. We developed a mathematical model of the xenophagy pathway to investigate this key defense mechanism. In this paper, we present a Petri net model of Salmonella xenophagy in epithelial cells. The model is based on functional information derived from literature data. It comprises the molecular mechanism of galectin-8-dependent and ubiquitin-dependent autophagy, including regulatory processes, like nutrient-dependent regulation of autophagy and TBK1-dependent activation of the autophagy receptor, OPTN. To model the activation of TBK1, we proposed a new mechanism of TBK1 activation, suggesting a spatial and temporal regulation of this process. Using standard Petri net analysis techniques, we found basic functional modules, which describe different pathways of the autophagic capture of Salmonella and reflect the basic dynamics of the system. To verify the model, we performed in silico knockout experiments. We introduced a new concept of knockout analysis to systematically compute and visualize the results, using an in silico knockout matrix. The results of the in silico knockout analyses were consistent with published experimental results and provide a basis for future investigations of the Salmonella xenophagy pathway.
Author Summary
Salmonellae are Gram-negative bacteria, which cause the majority of foodborne diseases worldwide. Serovars of Salmonella cause a broad range of diseases, ranging from diarrhea to typhoid fever in a variety of hosts. In the year 2010, Salmonella Typhi caused 7.6 million foodborne diseases and 52 000 deaths, and Salmonella enterica was responsible for 78.7 million diseases and 59 000 deaths. After invasion of Salmonella into host epithelial cells, a small fraction of Salmonella escapes from a specialized intracellular compartment and replicates inside the host cytosol. Xenophagy is a host defense mechanism to protect the host cell from cytosolic pathogens. Understanding how Salmonella is recognized and targeted for xenophagy is an important subject of current research. To the best of our knowledge, no mathematical model has been presented so far, describing the process of Salmonella Typhimurium xenophagy. Here, we present a manually curated and mathematically verified theoretical model of Salmonella Typhimurium xenophagy in epithelial cells, which is consistent with the current state of knowledge. Our model reproduces literature data and postulates new hypotheses for future investigations.
Rationale and Objectives: Lumbar disk degeneration is a common condition contributing significantly to back pain. The objective of the study was to evaluate the potential of dual-energy CT (DECT)-derived collagen maps for the assessment of lumbar disk degeneration.
Patients and Methods: We conducted a retrospective analysis of 127 patients who underwent dual-source DECT and MRI of the lumbar spine between 07/2019 and 10/2022. The level of lumbar disk degeneration was categorized by three radiologists as follows: no/mild (Pfirrmann 1&2), moderate (Pfirrmann 3&4), and severe (Pfirrmann 5). Recall (sensitivity) and accuracy of DECT collagen maps were calculated. Intraclass correlation coefficient (ICC) was used to evaluate inter-reader reliability. Subjective evaluations were performed using 5-point Likert scales for diagnostic confidence and image quality.
Results: We evaluated a total of 762 intervertebral disks from 127 patients (median age, 69.7 (range, 23.0–93.7), female, 56). MRI identified 230 non/mildly degenerated disks (30.2%), 484 moderately degenerated disks (63.5%), and 48 severely degenerated disks (6.3%). DECT collagen maps yielded an overall accuracy of 85.5% (1955/2286). Recall (sensitivity) was 79.3% (547/690) for the detection of no/mild lumbar disk degeneration, 88.7% (1288/1452) for the detection of moderate disk degeneration, and 83.3% (120/144) for the detection of severe disk degeneration (ICC = 0.9). Subjective evaluations of DECT collagen maps showed high diagnostic confidence (median 4) and good image quality (median 4).
Conclusion: The use of DECT collagen maps to distinguish different stages of lumbar disk degeneration may have clinical significance in the early diagnosis of disk-related pathologies in patients with contraindications for MRI or in cases of unavailability of MRI.
Rationale and Objectives: Bone non-union is a serious complication of distal radius fractures (DRF) that can result in functional limitations and persistent pain. However, no accepted method has been established to identify patients at risk of developing bone non-union yet. This study aimed to compare various CT-derived metrics for bone mineral density (BMD) assessment to identify predictive values for the development of bone non-union.
Materials and Methods: CT images of 192 patients with DRFs who underwent unenhanced dual-energy CT (DECT) of the distal radius between 03/2016 and 12/2020 were retrospectively identified. Available follow-up imaging and medical health records were evaluated to determine the occurrence of bone non-union. DECT-based BMD, trabecular Hounsfield unit (HU), cortical HU and cortical thickness ratio were measured in normalized non-fractured segments of the distal radius.
Results: Patients who developed bone non-union were significantly older (median age 72 years vs. 54 years) and had a significantly lower DECT-based BMD (median 68.1 mg/cm3 vs. 94.6 mg/cm3, p < 0.001). Other metrics (cortical thickness ratio, cortical HU, trabecular HU) showed no significant differences. ROC and PR curve analyses confirmed the highest diagnostic accuracy for DECT-based BMD with an area under the curve (AUC) of 0.83 for the ROC curve and an AUC of 0.46 for the PR curve. In logistic regression models, DECT-based BMD was the sole metric significantly associated with bone non-union.
Conclusion: DECT-derived metrics can accurately predict bone non-union in patients who sustained DRF. The diagnostic performance of DECT-based BMD is superior to that of HU-based metrics and cortical thickness ratio.