X-ray computed microtomography characterizes the wound effect that causes sap flow underestimation by thermal dissipation sensors.

Insertion of thermal dissipation (TD) sap flow sensors in living tree stems causes damage of the wood tissue, as is the case with other invasive methods. The subsequent wound formation is one of the main causes of underestimation of tree water-use measured by TD sensors. However, the specific alterations in wood anatomy in response to inserted sensors have not yet been characterized, and the linked dysfunctions in xylem conductance and sensor accuracy are still unknown. In this study, we investigate the anatomical mechanisms prompting sap flow underestimation and the dynamic process of wound formation. Successive sets of TD sensors were installed in the early, mid and end stage of the growing season in diffuse- and ring-porous trees, Fagus sylvatica (Linnaeus) and Quercus petraea ((Mattuschka) Lieblein), respectively. The trees were cut in autumn and additional sensors were installed in the cut stem segments as controls without wound formation. The wounded area and volume surrounding each sensor was then visually determined by X-ray computed microtomography (X-ray microCT). This technique allowed the characterization of vessel anatomical transformations such as tyloses formation, their spatial distribution and quantification of reduction in conductive area. MicroCT scans showed considerable formation of tyloses that reduced the conductive area of vessels surrounding the inserted TD probes, thus causing an underestimation in sap flux density (SFD) in both beech and oak. Discolored wood tissue was ellipsoidal, larger in the radial plane, more extensive in beech than in oak, and also for sensors installed for longer times. However, the severity of anatomical transformations did not always follow this pattern. Increased wound size with time, for example, did not result in larger SFD underestimation. This information helps us to better understand the mechanisms involved in wound effects with TD sensors and allows the provision of practical recommendations to reduce biases associated with wounding in field sap flow measurements.

Evaluation of cost and length of stay, linked to complications associated with major surgical procedures.

INTRODUCTION: A lot of studies have demonstrated the possibility of reducing the number of post-operative complications in the domain of major surgical procedures with the use of medical preventive techniques. However, complications following surgical procedures are unfortunately frequent and are a major problem, not only because of the impact for the patient, but also because of economic consequences that they provoke. The aim of the present study is to evaluate the extra length of stay and the extra cost, born by the hospital and the social security, linked to complications, incurring after major surgical procedures. MATERIAL AND METHODS: Study based on the data from 13 Belgian hospitals for the year 2012. Complications were extracted through medical discharge summaries. The cost born by the social security was assessed on the basis of the billing data, hospital cost are taken from cost accounting studies. RESULTS: The rate of complication for all the hospitals is 6.6%. About 30.3% of inpatient stays having a major or extreme severity of index had a complication during the stay, 1.8% of stays with a minor or moderate severity of index had a complication. The extra length of stay is 19.38 days when the stay has had a complication (p < 0.001). The additional mean cost borne from the hospital perspective is €21 353.07 and €8 026.65 for the social security. This additional mean cost varies greatly from one hospital to another. DISCUSSION/CONCLUSION: The present study has shown that the actual financing do not cover real hospital costs in the field of major surgical procedures having caused complications. Results should encourage Belgian authorities to propose and finance preventive measures in order to reduce these complications, which represent major economic impacts, not only for authorities but also for hospitals.

Comparison of species classification models of mass spectrometry data: Kernel Discriminant Analysis vs Random Forest; A case study of Afrormosia (Pericopsis elata (Harms) Meeuwen).

RATIONALE: The genus Pericopsis includes four tree species of which only Pericopsis elata (Harms) Meeuwen is of commercial interest. Enforcement officers might have difficulties discerning this CITES-listed species from some other tropical African timber species. Therefore, we tested several methods to separate and identify these species rapidly in order to enable customs officials to uncover illegal trade. In this study, two classification methods using Direct Analysis in Real Time (DART™) ionization coupled with Time-of-Flight Mass Spectrometry (DART-TOFMS) data to discern between several species are presented. METHODS: Metabolome profiles were collected using DART™ ionization coupled with TOFMS analysis of heartwood specimens of all four Pericopsis species and Haplormosia monophylla (Harms) Harms, Dalbergia melanoxylon Guill. & Perr. Harms, and Milicia excelsa (Welw.) C.C. Berg. In total, 95 specimens were analysed and the spectra evaluated. Kernel Discriminant Analysis (KDA) and Random Forest classification were used to discern the species. RESULTS: DART-TOFMS spectra obtained from wood slivers and post-processing analysis using KDA and Random Forest classification separated Pericopsis elata from the other Pericopsis taxa and its lookalike timbers Haplormosia monophylla, Milicia excelsa, and Dalbergia melanoxylon. Only 50 ions were needed to achieve the highest accuracy. CONCLUSIONS: DART-TOFMS spectra of the taxa were reproducible and the results of the chemometric analysis provided comparable accuracy. Haplormosia monophylla was visually distinguished based on the heatmap and was excluded from further analysis. Both classification methods, KDA and Random Forest, were capable of distinguishing Pericopsis elata from the other Pericopsis taxa, Milicia excelsa, and Dalbergia melanoxylon, timbers that are commonly traded.

Modelling three-dimensional fungal growth in response to environmental stimuli.

Most fungi grow by developing complex networks that enable the translocation of nutrients over large distances. Spatially explicit mathematical models are able to capture both the complexity of the fungal network and the biomass evolution, as such providing a powerful alternative to classical modelling paradigms. Unfortunately, most of these models restrict growth to two dimensions or confine it to a lattice, thereby resulting in unrealistic representations of fungal networks. In addition, interactions between fungi and their environment are often neglected. In response, this work presents a lattice-free three-dimensional fungal growth model that accounts for the interactions between the in silico fungus and different substrates and media. A sensitivity analysis was carried out to identify the key model parameters for future calibration. Finally, a scenario analysis covering a variety of growth conditions was conducted to illustrate the broad scope of the model and its ability to replicate in situ growth scenarios.

Automated image-based analysis of spatio-temporal fungal dynamics.

Due to their ability to grow in complex environments, fungi play an important role in most ecosystems and have for that reason been the subject of numerous studies. Some of the main obstacles to the study of fungal growth are the heterogeneity of growth environments and the limited scope of laboratory experiments. Given the increasing availability of image capturing techniques, a new approach lies in image analysis. Most previous image analysis studies involve manual labelling of the fungal network, tracking of individual hyphae, or invasive techniques that do not allow for tracking the evolution of the entire fungal network. In response, this work presents a highly versatile tool combining image analysis and graph theory to monitor fungal growth through time and space for different fungal species and image resolutions. In addition, a new experimental set-up is presented that allows for a functional description of fungal growth dynamics and a quantitative mutual comparison of different growth behaviors. The presented method is completely automated and facilitates the extraction of the most studied fungal growth features such as the total length of the mycelium, the area of the mycelium and the fractal dimension. The compactness of the fungal network can also be monitored over time by computing measures such as the number of tips, the node degree and the number of nodes. Finally, the average growth angle and the internodal length can be extracted to study the morphology of the fungi. In summary, the introduced method offers an updated and broader alternative to classical and narrowly focused approaches, thus opening new avenues of investigation in the field of mycology.