Local grassland restoration affects insect communities

1. It is hypothesised that ecological restoration in grasslands can induce an alternative stable state shift in vegetation. The change in vegetation influences insect community assemblages and allows for greater functional redundancy in pollination and refuge for native insect species. 2. Insect community assemblages at eight coastal California grassland sites were evaluated. Half of these sites had undergone restoration through active revegetation of native grassland flora and half were non‐restored. Insects were collected from Lupinus bicolor (Fabaceae) within 2 × 2‐m² plots in spring 2017. Lupinus bicolor is a common native species that is used in California restoration projects, and home and state landscaping projects. 3. Ordination demonstrated that insect community assemblages were different between restored and non‐restored sites. These differences were seen in insect functional groups as well as taxa‐specific differences and were found to be driven by environmental characteristics such as non‐native forb cover. 4. Functional redundancy of herbivores decreased at restored sites, while pollinators became more redundant compared with non‐restored sites. The assemblages of the common species found at restoration sites contained more native insects than those found at non‐restored sites, including species such as Bombus vosnesenskii. 5. Local grassland restoration has the potential to induce an alternative stable state change and affect insect community assemblages. Additionally, it was found that grassland restoration can be a potential conservation tool to provide refugia for bumblebees (Bombus), but additional studies are required to fully understand its broader applicability.     

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.     

Isomeric lipid signatures reveal compartmentalized fatty acid metabolism in cancer

The cellular energy and biomass demands of cancer drive a complex dynamic between uptake of extracellular FAs and their de novo synthesis. Given that oxidation of de novo synthesized FAs for energy would result in net-energy loss, there is an implication that FAs from these two sources must have distinct metabolic fates; however, hitherto, all FAs have been considered part of a common pool. To probe potential metabolic partitioning of cellular FAs, cancer cells were supplemented with stable isotope-labeled FAs. Structural analysis of the resulting glycerophospholipids revealed that labeled FAs from uptake were largely incorporated to canonical (sn-) positions on the glycerol backbone. Surprisingly, labeled FA uptake also disrupted canonical isomer patterns of the unlabeled lipidome and induced repartitioning of n-3 and n-6 PUFAs into glycerophospholipid classes. These structural changes support the existence of differences in the metabolic fates of FAs derived from uptake or de novo sources and demonstrate unique signaling and remodeling behaviors usually hidden from conventional lipidomics.     

Evaluation of four-dimensional cone beam computed tomography ventilation images acquired with two different linear accelerators at various gantry speeds using a deformable lung phantom

We evaluated four-dimensional cone beam computed tomography (4D-CBCT) ventilation images (VI_CBCT) acquired with two different linear accelerator systems at various gantry speeds using a deformable lung phantom.The 4D-CT and 4D-CBCT scans were performed using a computed tomography (CT) scanner, an X-ray volume imaging system (Elekta XVI) mounted in Versa HD, and an On-Board Imager (OBI) system mounted in TrueBeam. Intensity-based deformable image registration (DIR) was performed between peak-exhale and peak-inhale images. VI_CBCT- and 4D-CT-based ventilation images (VI_CT) were derived by DIR using two metrics: one based on the Jacobian determinant and one on changes in the Hounsfield unit (HU). Three different DIR regularization values (λ) were used for VI_CBCT. Correlations between the VI_CBCT and VI_CT values were evaluated using voxel-wise Spearman’s rank correlation coefficient (r).In case of both metrics, the Jacobian-based VI_CBCT with a gantry speed of 0.6 deg/sec in Versa HD showed the highest correlation for all the gantry speeds (e.g., λ = 0.05 and r = 0.68). Thus, the r value of the Jacobian-based VI_CBCT was greater or equal to that of the HU-based VI_CBCT. In addition, the ventilation accuracy of VI_CBCT increased at low gantry speeds.Thus, the image quality of VI_CBCT was affected by the change in gantry speed in both the imaging systems. Additionally, DIR regularization considerably influenced VI_CBCT in both the imaging systems. Our results have the potential to assist in designing CBCT protocols, incorporating VI_CBCT imaging into the functional avoidance planning process.     

In vitro dynamics of chromatin organization and migration

The organization of eukaryotic chromatin is not static but changes as a function of cell status during processes such as proliferation, differentiation, and migration. DNA quantification has not been used extensively to investigate chromatin dynamics in combination with cellular migration. In this context, an optimized DNA-specific, nonperturbant method has been developed for studying chromatin organization, using the fluorescent vital bisbenzimidazole probe Hoechst 33342: this property has been described by Hamori et al. (1980). Computer-assisted image analysis was used to follow migratory activity and chromatin organization of L929 fibroblasts during in vitro wound healing. Cell movements were analyzed using an optical flow technique, which consists in the calculation of the velocity field of cells and nuclear movements in the frame. This system allows the correlation of cell migration and position in the cell cycle. It makes it possible to study chromatin dynamics using a quantitative analysis of nuclear differentiation reorganization (nuclear texture) and to correlate this with migration characteristics. The present system would be of interest for studying cell-extracellular matrix interactions using differing substrates, and also the migratory response to chemotactic factors. Such a model is a prerequisite for gaining better understanding of drug action.     

Does Weeding Promote Regeneration of an Indigenous Tree Community in Felled Pine Plantations in Uganda?

The use of plantations to manage extensive tracks of deforested lands in the tropics is a conservation strategy that has recently received considerable attention. Plantation trees can promote seed dispersal by attracting dispersers and creating favorable site conditions, leading to increased germination and establishment of indigenous trees. Subsequently, plantation trees can be harvested for profit or left to senesce, leaving a native tree community. We evaluated the effect of vine, grass, and shrub cutting (weeding) over a 3‐year period on regeneration of indigenous trees subsequent to the removal of plantation softwoods in Kibale National Park, Uganda. Counter to what would be expected if weeding released trees from competition, we found no difference in the total number of stems or in the stems greater than 10 cm diameter at breast height between control and weeded plots; there were more stems greater than 1 cm diameter at breast height in the control plots. For species found in both control and weeded plots, the maximum size of individuals did not differ. At the end of the study, 61 species were found in the control plots and 43 species were found in the weeded plots, and in both types of plots the three most abundant species were the same. The number of species and stems classified as early or middle successional species did not differ between weeded and control plots. The fact that weeding did not promote regeneration of indigenous trees after the removal of plantation trees illustrates the importance of evaluating and field‐testing potential management options.     

Dream Imagery and Emotion.

The relationship between prominent visual imagery and emotion within dreams was investigated in relation to E. Hartmann's (1996) contextualizing image (CI) theory and M. Seligman and A. Yellen's (1987) dual imagery theory. Fifty-nine students recorded dreams over a 2-week period and submitted 115 dreams for analysis. Participants recorded ratings of emotion type and emotion intensity in each scene. Prominent visual images were identified and scored for intensity and detail by independent judges. As hypothesized from Hartmann's theory, there was a significant positive relationship between CI intensity and emotion intensity in the CI scene, emotion intensity generally peaked in the CI scene, and dreams containing a CI had higher overall ratings of emotion intensity than non-CI dreams. The result for the correlation of detail of prominent imagery with emotion was inconclusive, with a low positive correlation across CI scenes. This raises the possibility that the CI is not a unitary construct. (PsycINFO Database Record (c) 2010 APA, all rights reserved)