Roberto Monetti

Successful and safe use of 2 min cold atmospheric argon plasma in chronic wounds: results of a randomized controlled trial

Background  The development of antibiotic resistance by microorganisms is an increasing problem in medicine. In chronic wounds, bacterial colonization is associated with impaired healing. Cold atmospheric plasma is an innovative promising tool to deal with these problems.

Label-Free Live-Cell Imaging with Confocal Raman Microscopy

Confocal Raman spectroscopy is a noninvasive alternative to established cell imaging methods because it does not require chemical fixation, the use of fluorescent markers, or genetic engineering. In particular, single live-cell, high-resolution imaging by confocal Raman microscopy is desirable because it allows further experiments concerning the individually investigated cells. However, to derive meaningful images from the spectroscopic data, one must identify cell components within the dataset. Using immunofluorescence images as a reference, we derive Raman spectral signatures by means of information measures to identify cell components such as the nucleus, the endoplasmic reticulum, the Golgi apparatus, and mitochondria. The extracted signatures allow us to generate representations equivalent to conventional (immuno)fluorescence images with more than three cell components at a time, exploiting the Raman spectral information alone.

Long-term persistence in the sea surface temperature fluctuations

We study the temporal correlations in the sea surface temperature (SST) fluctuations around the seasonal mean values in the Atlantic and Pacific Oceans. We apply a method that systematically overcome possible trends in the data. We find that the SST persistence, characterized by the correlation C(s) of temperature fluctuations separated by a time period s, displays two different regimes. In the short-time regime which extends up to roughly 10 months, the temperature fluctuations display a non-stationary behavior for both oceans, while in the asymptotic regime it becomes stationary. The long-term correlations decay as C(s)∼s−γ with γ∼0.4 for both oceans which is different from γ∼0.7 found for atmospheric land temperature.

Automated 3D trabecular bone structure analysis of the proximal femur—prediction of biomechanical strength by CT and DXA

SummaryThe standard diagnostic technique for assessing osteoporosis is dual X-ray absorptiometry (DXA) measuring bone mass parameters. In this study, a combination of DXA and trabecular structure parameters (acquired by computed tomography [CT]) most accurately predicted the biomechanical strength of the proximal femur and allowed for a better prediction than DXA alone.IntroductionAn automated 3D segmentation algorithm was applied to determine specific structure parameters of the trabecular bone in CT images of the proximal femur. This was done to evaluate the ability of these parameters for predicting biomechanical femoral bone strength in comparison with bone mineral content (BMC) and bone mineral density (BMD) acquired by DXA as standard diagnostic technique.MethodsOne hundred eighty-seven proximal femur specimens were harvested from formalin-fixed human cadavers. BMC and BMD were determined by DXA. Structure parameters of the trabecular bone (i.e., morphometry, fuzzy logic, Minkowski functionals, and the scaling index method [SIM]) were computed from CT images. Absolute femoral bone strength was assessed with a biomechanical side-impact test measuring failure load (FL). Adjusted FL parameters for appraisal of relative bone strength were calculated by dividing FL by influencing variables such as body height, weight, or femoral head diameter.ResultsThe best single parameter predicting FL and adjusted FL parameters was apparent trabecular separation (morphometry) or DXA-derived BMC or BMD with correlations up to r = 0.802. In combination with DXA, structure parameters (most notably the SIM and morphometry) added in linear regression models significant information in predicting FL and all adjusted FL parameters (up to Radj = 0.872) and allowed for a significant better prediction than DXA alone.ConclusionA combination of bone mass (DXA) and structure parameters of the trabecular bone (linear and nonlinear, global and local) most accurately predicted absolute and relative femoral bone strength.

Randomized placebo-controlled human pilot study of cold atmospheric argon plasma on skin graft donor sites

Cold atmospheric plasma has already been shown to decrease the bacterial load in chronic wounds. However, until now it is not yet known if plasma treatment can also improve wound healing. We aimed to assess the impact of cold atmospheric argon plasma on the process of donor site healing. Forty patients with skin graft donor sites on the upper leg were enrolled in our study. The wound sites were divided into two equally sized areas that were randomly assigned to receive either plasma treatment or placebo (argon gas) for 2 minutes. Donor site healing was evaluated independently by two blinded dermatologists, who compared the wound areas with regard to reepithelialization, blood crusts, fibrin layers, and wound surroundings. From the second treatment day onwards, donor site wound areas treated with plasma (n = 34) showed significantly improved healing compared with placebo‐treated areas (day 1, p = 0.25; day 2, p = 0.011; day 3, p < 0.001; day 4, p < 0.001; day 5, p = 0.004; day 6, p = 0.008; day 7, p = 0.031). Positive effects were observed in terms of improved reepithelialization and fewer fibrin layers and blood crusts, whereas wound surroundings were always normal, independent of the type of treatment. Wound infection did not occur in any of the patients, and no relevant side effects were observed. Both types of treatment were well tolerated. The mechanisms contributing to these clinically observed effects should be further investigated.

Local 3D scaling properties for the analysis of trabecular bone extracted from high-resolution magnetic resonance imaging of human trabecular bone : Comparison with bone mineral density in the prediction of biomechanical strength in vitro

Rationale and Objectives. A novel, nonlinear morphologic measure [&Dgr;P(&agr;)] based on local 3D scaling properties was applied to high-resolution magnetic resonance images (HR-MRI) of human trabecular bone to predict biomechanical strength in vitro. Methods. We extracted &Dgr;P(&agr;) and traditional morphologic parameters (apparent trabecular volume fraction, apparent trabecular separation) from HR-MR images of 32 femoral and 13 spinal bone specimens. Furthermore, bone mineral density (BMD) and maximum compressive strength (MCS) were determined. The morphologic measures were compared with BMD in predicting the biomechanical strength. Results. In the vertebral (femoral) specimens, R2 for MCS versus &Dgr;P(&agr;) was 0.87 (0.61) (P < 0.001). Correlation between BMD and MCS was 0.53 (P = 0.05) (0.79 [P < 0.001]) for the vertebral (femoral) specimens. For the femoral specimens, prediction of MCS could be improved further by combining BMD and morphologic parameters by multiple regression (R2 = 0.88). Conclusions. Morphologic measures extracted from HR-MRI considering local 3D-scaling properties can be used to predict biomechanical properties of bone in vitro. They are superior to 2-dimensional standard linear morphometric measures and, depending on the anatomic location, more reliably predict bone strength as measured by MCS than does BMD.

Strength through structure: visualization and local assessment of the trabecular bone structure

The visualization and subsequent assessment of the inner human bone structures play an important role for better understanding the disease- or drug-induced changes of bone in the context of osteoporosis giving prospect for better predictions of bone strength and thus of the fracture risk of osteoporotic patients. In this work, we show how the complex trabecular bone structure can be visualized using μCT imaging techniques at an isotropic resolution of 26 μm. We quantify these structures by calculating global and local topological and morphological measures, namely Minkowski functionals (MFs) and utilizing the (an-)isotropic scaling index method (SIM) and by deriving suitable texture measures based on MF and SIM. Using a sample of 151 specimens taken from human vertebrae in vitro, we correlate the texture measures with the mechanically measured maximum compressive strength (MCS), which quantifies the strength of the bone probe, by using Pearsons correlation coefficient. The structure parameters derived from the local measures yield good correlations with the bone strength as measured in mechanical tests. We investigate whether the performance of the texture measures depends on the MCS value by selecting different subsamples according to MCS. Considering the whole sample the results for the newly defined parameters are better than those obtained for the standard global histomorphometric parameters except for bone volume/total volume (BV/TV). If a subsample consisting only of weak bones is analysed, the local structural analysis leads to similar and even better correlations with MCS as compared to BV/TV. Thus, the MF and SIM yield additional information about the stability of the bone especially in the case of weak bones, which corroborates the hypothesis that the bone structure (and not only its mineral mass) constitutes an important component of bone stability.

Information directionality in coupled time series using transcripts.

In ordinal symbolic dynamics, transcripts describe the algebraic relationship between ordinal patterns. Using the concept of transcript, we exploit the mathematical structure of the group of permutations to derive properties and relations among information measures of the symbolic representations of time series. These theoretical results are then applied for the assessment of coupling directionality in dynamical systems, where suitable coupling directionality measures are introduced depending only on transcripts. These measures improve the reliability of the information flow estimates and reduce to well-established coupling directionality quantifiers when some general conditions are satisfied. Furthermore, by generalizing the definition of transcript to ordinal patterns of different lengths, several of the commonly used information directionality measures can be encompassed within the same framework.

Scaling analysis of trends using DFA

We study two aspects of the detrended fluctuation analysis (DFA) method, namely the scaling behavior of the leading terms of the best-fit polynomials and the detection of trends. We show analytically and numerically that the standard deviation of the leading terms of the best-fit polynomials used in DFA displays scaling behavior. Furthermore, we demonstrate that the distribution of these terms can be used to reveal the presence of trends in the data. We also argue that this distribution can be used as a sensitive tool for identifying weak trends.

Transcripts: An algebraic approach to coupled time series

Ordinal symbolic dynamics is based on ordinal patterns. Its tools include permutation entropy (in metric and topological versions), forbidden patterns, and a number of mathematical results that make this sort of symbolic dynamics appealing both for theoreticians and practitioners. In particular, ordinal symbolic dynamics is robust against observational noise and can be implemented with low computational cost, which explains its increasing popularity in time series analysis. In this paper, we study the perhaps less exploited aspect so far of ordinal patterns: their algebraic structure. In a first part, we revisit the concept of transcript between two symbolic representations, generalize it to N representations, and derive some general properties. In a second part, we use transcripts to define two complexity indicators of coupled dynamics. Their performance is tested with numerical and real world data.