Background Major incidents are characterized by a lack of resources compared to an overwhelming number of casualties, requiring a prioritization of medical treatment. Triage algorithms are an essential tool for prioritizing the urgency of treatment for patients, but the evidence to support one over another is very limited. We determined the influence of blood pressure limits on the diagnostic value of triage algorithms, considering if pulse should be palpated centrally or peripherally. Methods We used a database representing 500 consecutive HEMS patients. Each patient was allocated a triage category (T1/red, T2/yellow, T3/green) by a group of experienced doctors in disaster medicine, independent of any algorithm. mSTaRT, ASAV, Field Triage Score (FTS), Care Flight (CF), “Model Bavaria” and two Norwegian algorithms (Nor and TAS), all containing the question “Pulse palpable?”, were translated into Excel commands, calculating the triage category for each patient automatically. We used 5 blood pressure limits ranging from 130 to 60 mmHg to determine palpable pulse. The resulting triage categories were analyzed with respect to sensitivity, specificity and Youden Index (J) separately for trauma and non-trauma patients, and for all patients combined. Results For the entire population of patients within all triage algorithms the Youden Index (J) was highest for T1 (J between 0,14 and 0,62). Combining trauma and non-trauma patients, the highest J was obtained by ASAV (J = 0,62 at 60 mmHg). ASAV scored the highest within trauma patients (J = 0,87 at 60 mmHg), whereas Model Bavaria (J = 0,54 at 80 mmHg) reached highest amongst non-trauma patients. FTS performed worst for all patients (J = 0,14 at 60 mmHg), showing a lower score for trauma patients (J = 0,0 at 60 mmHg). Change of blood pressure limits resulted in different diagnostic values of all algorithms. Discussion We demonstrate that differing blood pressure limits have a remarkable impact on diagnostic values of triage algorithms. Further research is needed to determine the lowest blood pressure value that is possible to palpate at a peripheral artery compared to a central artery. Conclusion As a consequence, it might be important in which location pulses are palpated according to the algorithm at hand during triage of patients.

Many diffusion processes in nature and society were found to be anomalous, in the sense of being fundamentally different from conventional Brownian motion. An important example is the migration of biological cells, which exhibits non-trivial temporal decay of velocity autocorrelation functions. This means that the corresponding dynamics is characterized by memory effects that slowly decay in time. Motivated by this we construct non-Markovian lattice-gas cellular automata models for moving agents with memory. For this purpose the reorientation probabilities are derived from velocity autocorrelation functions that are given a priori; in that respect our approach is “data-driven”. Particular examples we consider are velocity correlations that decay exponentially or as power laws, where the latter functions generate anomalous diffusion. The computational efficiency of cellular automata combined with our analytical results paves the way to explore the relevance of memory and anomalous diffusion for the dynamics of interacting cell populations, like confluent cell monolayers and cell clustering.

In patients with Parkinson’s disease (PD), the molecularly misfolded form of α-synuclein was recently identified in cutaneous autonomic nerve fibers which displayed increased accumulation even in early disease stages. However, the underlying mechanisms of synucleinopathic nerve damage and its implication for brain pathology in later life remain to be elucidated. To date, specific diagnostic tools to evaluate small fiber pathology and to discriminate neurodegenerative proteinopathies are rare. Recently, research has indicated that deposition of α-synuclein in cutaneous nerve fibers quantified via immunohistochemistry in superficial skin biopsies might be a valid marker of PD which could facilitate early diagnosis and monitoring of disease progression. However, lack of standardization of techniques to quantify neural α-synuclein deposition limits their utility in clinical practice. Additional challenges include the identification of potential distinct morphological patterns of intraneural α-synuclein deposition among synucleinopathies to facilitate diagnostic discrimination and determining the degree to which structural damage relates to dysfunction of nerve fibers targeted by α-synuclein. Answering these questions might improve our understanding of the pathophysiological role of small fiber neuropathy in Parkinson’s disease, help identify new treatment targets, and facilitate assessment of response to neuroprotective treatment.

During neocortical development, network activity undergoes a dramatic transition from largely synchronized, so-called cluster activity, to a relatively sparse pattern around the time of eye-opening in rodents. Biophysical mechanisms underlying this sparsification phenomenon remain poorly understood. Here, we present a dynamic systems modeling study of a developing neural network that provides the first mechanistic insights into sparsification. We find that the rest state of immature networks is strongly affected by the dynamics of a transient, unstable state hidden in their firing activities, allowing these networks to either be silent or generate large cluster activity. We address how, and which, specific developmental changes in neuronal and synaptic parameters drive sparsification. We also reveal how these changes refine the information processing capabilities of an in vivo developing network, mainly by showing a developmental reduction in the instability of network’s firing activity, an effective availability of inhibition-stabilized states, and an emergence of spontaneous attractors and state transition mechanisms. Furthermore, we demonstrate the key role of GABAergic transmission and depressing glutamatergic synapses in governing the spatiotemporal evolution of cluster activity. These results, by providing a strong link between experimental observations and model behavior, suggest how adult sparse coding networks may emerge developmentally.

Background The revitalization or regeneration of the dental pulp is a preferable goal in current endodontic research. In this study, human dental pulp cell (DPC) spheres were applied to human root canal samples to evaluate their potential adoption for physiological tissue-like regeneration of the dental root canal by odontoblastic differentiation as well as cell-induced mineral formation. Methods DPC were cultivated into three-dimensional cell spheres and seeded on human root canal specimens. The evaluation of sphere formation, tissue-like behavior and differentiation as well as mineral formation of the cells was carried out with the aid of optical light microscopy, immunohistochemical staining and scanning electron microscopy (SEM). Results Spheres and cells migrated out of the spheres showed an intense cell-cell- and cell-dentin-contact with the formation of extra cellular matrix. In addition, the ingrowth of cell processes into dentinal tubules and the interaction of cell processes with the tubule walls were detected by SEM-imaging. Immunohistochemical staining of the odontoblast specific matrix proteins, dentin matrix protein-1, and dentin sialoprotein revealed an odontoblast-like cell differentiation in contact with the dentin surface. This differentiation was confirmed by SEM-imaging of cells with an odontoblast specific phenotype and cell induced mineral formation. Conclusions The results of the present study reveal the high potential of pulp cells organized in spheres for dental tissue engineering. The odontoblast-like differentiation and the cell induced mineral formation display the possibility of a complete or partial “dentinal filling” of the root canal and the opportunity to combine this method with other current strategies.

One problem in cooperative game theory is to model situations when two players refuse to cooperate (or the problem of quarreling members in coalitions). One example of such exclusions is the coalition statements of parliamentary parties. Other situations in which incompatible players affect the outcome are teams in firms and markets, for example. To model these exclusions in cooperative game theory, the excluded coalitions value ( φE value) was introduced. This value is based on the Shapley value and takes into account that players exclude coalitions with other players. In this article, we deduce some properties of this new value. After some general results, we analyze the apex game that could be interpreted as a team situation and the glove game that models markets where sellers and buyers deal. For team situations, we show that all employees have a common interest for cooperation. On asymmetric markets, excluding coalitions affect the market players of the scarce side to a higher extent.

The topology of interactions in network dynamical systems fundamentally underlies their function. Accelerating technological progress creates massively available data about collective nonlinear dynamics in physical, biological, and technological systems. Detecting direct interaction patterns from those dynamics still constitutes a major open problem. In particular, current nonlinear dynamics approaches mostly require to know a priori a model of the (often high dimensional) system dynamics. Here we develop a model-independent framework for inferring direct interactions solely from recording the nonlinear collective dynamics generated. Introducing an explicit dependency matrix in combination with a block-orthogonal regression algorithm, the approach works reliably across many dynamical regimes, including transient dynamics toward steady states, periodic and non-periodic dynamics, and chaos. Together with its capabilities to reveal network (two point) as well as hypernetwork (e.g., three point) interactions, this framework may thus open up nonlinear dynamics options of inferring direct interaction patterns across systems where no model is known.

BACKGROUND: In order to better understand the multifactorial nature of osteoporosis, animal models are utilized and compared to healthy controls. Female sheep are well established as a model for osteoporosis induced by ovariectomy, calcium and vitamin D low diet, application of steroids, or a combination of these treatments. Transcriptional studies can be performed by applying quantitative real time PCR (RT-qPCR). RT-qPCR estimates mRNA-levels of target genes in relation to reference genes. A chosen set of reference genes should not show variation under experimental conditions. Currently, no standard reference genes are accepted for all tissue types and experimental conditions. Studies examining reference genes for sheep are rare and only one study described stable reference in mandibular bone. However, this type of bone differs from trabecular bone where most osteoporotic fractures occur. The present study aimed at identifying a set of reference genes for relative quantification of transcriptional activity of ovine spine bone and ovine in vitro differentiated mesenchymal stromal cells (MSC) for reliable comparability. METHODS: Twelve candidate reference genes belonging to different functional classes were selected and their expression was measured from cultured ovMSCs (n = 18) and ovine bone samples (n = 16), respectively. RefFinder was used to rank the candidate genes. RESULTS: We identified B2M, GAPDH, RPL19 and YWHAZ as the best combination of reference genes for normalization of RT-qPCR results for transcriptional analyses of these ovine samples. CONCLUSION: This study demonstrates the importance of applying a set of reference genes for RT-qPCR analysis in sheep. Based on our data we recommend using four identified reference genes for relative quantification of gene expression studies in ovine bone or for in vitro experiments with osteogenically differentiated ovine MSCs.

Background To investigate vascular-related pathophysiological characteristics of two human lung cancers with modifiable vascularisation using MRI and CT. Methods Tumour xenografts with modifiable vascularisation were established in 71 rats (approval by the Animal Care Committee was obtained) by subcutaneous transplantation of two human non-small-cell lung cancer (NSCLC) cells (A549, H1299) either alone or co-transplanted with vascular growth promoters. The vascularity of the tumours was assessed noninvasively by MRI diffusion-weighted-imaging (DWI), T2-weighted, and time-of-flight (TOF) sequences) as well as contrast-enhanced CT (CE-CT), using clinical scanners. As a reference standard, histological examinations (CD-31, fluorescent beads) were done after explantation. Results Microvessel density (MVD) was higher in co-transplanted tumours (171 ± 19 number/mm2) than in non-co-transplanted tumours (111 ± 11 number/mm2; p = 0.002). Co-transplanted tumours showed higher growth rates and larger tumour vessels at TOF-MRI as well as larger necrotic areas at CE-CT. In co-transplanted tumours, DWI revealed higher cellularity (lower minimal ADCdiff 166 ± 15 versus 346 ± 27 mm2/s × 10−6; p < 0.001), highly necrotic areas (higher maximal ADCdiff 1695 ± 65 versus 1320 ± 59 mm2/s × 10−6; p < 0.001), and better-perfused tumour stroma (higher ADCperf 723 ± 36 versus 636 ± 51 mm2/s × 10−6; p = 0.005). Significant correlations were found using qualitative and quantitative parameters: maximal ADCperf and MVD (r = 0.326); maximal ADCdiff and relative necrotic volume on CE-CT (r = 0.551); minimal ADCdiff and MVD (r = −0.395). Conclusions Pathophysiological differences related to vascular supply in two human lung cancer cell lines with modifiable vascularity are quantifiable with clinical imaging techniques. Imaging parameters of vascularisation correlated with the results of histology. DWI was able to characterise both the extent of necrosis and the level of perfusion.

The subject of this splitted article is the commissioning of a new application that may be part of a processing machine. Considering the example of the intermittent transport of small-sized goods, for example, chocolate bars, ideas for increasing the maximum performance are discussed. Starting from an analysis, disadvantages of a conventional motion approach are discussed, and thus, a new motion approach is presented. For realising this new motion approach, a virtual process model has to be built, which is the subject of this article. Therefore, the real process has to be abstracted, so only the main elements take attention in the modelling process. Following, important model parameters are determined and verified using virtual experiments. This finally leads to the possibility to calculate useful operating speed–dependent trajectories using the process model.