Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

Distribution of plant functional types along gradients of disturbance intensity and resource supply in an agricultural landscape

Abstract. In this study, plant functional types are understood as groups of plants with similar biological traits displaying significant optima or maxima on a gradient plane of resource supply and disturbance intensity. The biological traits refer to expansion, vegetative regeneration, generative reproduction, dispersal and seed bank longevity. 129 vegetation samples were taken in an agricultural landscape in southwestern Germany, covering a wide range of terrestrial vegetation types – but with the exception of forests and wetlands. For each site, also soil data were recorded. Mean daily soil moisture was estimated with a simple model. Soil moisture, balanced nitrogen supply and available phosphorus were combined into a factor ‘resource supply’. In addition, disturbance intensity was estimated for each site. This factor was based on (1) frequency of disturbance, (2) disturbance depth below or above the soil surface, and (3) proportion of the area affected by a discrete disturbance event. 30 plant groups with similar biological characteristics resulted from a cluster analysis, based on a compilation of 19 biological traits for a regional species pool. Logistic regression on a gradient plane of disturbance intensity and resource supply yielded response curves for 28 groups. The dependent variable was defined as the probability of encountering all members of a group in a sample. 17 groups display a significant response curve on the gradient plane. Plants with a potential for long- range dispersal are concentrated on sites with low or high disturbance intensities (e.g. fallow land, fields, lawns). On sites with medium disturbance intensity (e.g. meadows) and low to medium resource supply, small-range dispersal predominates. There are no distinct trends concerning seed bank longevity. The potential for vertical and lateral expansion increases with decreasing disturbance intensity. Only at medium disturbance intensities does vertical expansion correlate positively with resource supply. Rapid detachment of daughter individuals occurs more often on productive sites than on less productive sites. Diversity of groups with similar biological traits is highest on sites with medium disturbance intensities.     

Can landscape properties predict occurrence of grey-sided voles?

There has been a long-term decline in spring and fall numbers of Clethrionomys rufocanus in boreal Sweden in 1971–2005. Previous studies on permanent sampling plots in the centre of 2.5 × 2.5 km landscapes suggested that habitat fragmentation (sensu destruction) could have contributed to the decline. Therefore, we tested these findings in a field study and compared trapping results on the central sampling plots of landscapes with a low degree of fragmentation (LDF) and of “hot spot” type with trapping results in managed forest landscapes with a high degree of fragmentation (HDF). We predicted that C. rufocanus would be more common on the LDF plots. We used our permanent plots supplemented with a new sample of plots, mainly of the rare LDF type, inside or just outside the long-term study area. Very few voles were trapped on both plot types, and no difference was found. However, a subsequent pilot study with trapping in a national park with large areas of pristine, unfragmented forest yielded more voles than in the managed, more fragmented, areas. Consequently, the initial field study data and some other recent data were also re-analysed from a “local patch quality” perspective. This alternative approach revealed the positive importance of large focal patches of forest >60 years old and their content of old-growth (pine) forest (>100 years). Interestingly, at the landscape level, the frequency distribution of patches of forest >60 years old, old-growth (>100 years), and especially of old-growth pine forest (>100 years), relative to the properties of plots with C. rufocanus, suggested that there are few forest patches left that are suitable for C. rufocanus. Our current results suggest that habitat fragmentation cannot be excluded as a contributing cause to the long-term decline of C. rufocanus in boreal Sweden.     

Non-random distribution of individual genetic diversity along an environmental gradient

Improving our knowledge of the links between ecology and evolution is especially critical in the actual context of global rapid environmental changes. A critical step in that direction is to quantify how variation in ecological factors linked to habitat modifications might shape observed levels of genetic variability in wild populations. Still, little is known on the factors affecting levels and distribution of genetic diversity at the individual level, despite its vital underlying role in evolutionary processes. In this study, we assessed the effects of habitat quality on population structure and individual genetic diversity of tree swallows (Tachycineta bicolor) breeding along a gradient of agricultural intensification in southern Québec, Canada. Using a landscape genetics approach, we found that individual genetic diversity was greater in poorer quality habitats. This counter-intuitive result was partly explained by the settlement patterns of tree swallows across the landscape. Individuals of higher genetic diversity arrived earlier on their breeding grounds and settled in the first available habitats, which correspond to intensive cultures. Our results highlight the importance of investigating the effects of environmental variability on individual genetic diversity, and of integrating information on landscape structure when conducting such studies.