Insect ecology and veteran trees

Insect and veteran trees are important parts of ecosystems and are usually included in ecological studies of forest management. The loss of veteran trees in woodlands and open landscapes would lead to the loss of saproxylic organisms—an important part of biodiversity. Hence, the persistence of many specialized insects depends on the presence of veteran trees scattered in woodlands (e.g. ancient wood pastures, game parks or protected areas), cities, towns and villages (e.g. avenues, parks or chateau parks) or open landscapes (e.g. fishpond dams, solitary trees or fruit orchards). Veteran tree conditions could be fairly well described by three components—diameter, age and microhabitats present. The problem is that diameter belongs to the most studied characteristics, while age and microhabitats, which can be quite complicated to measure, are much less studied. This paper illustrates that, due to this unbalanced use of indicators of veteran-tree conditions, we are still missing some important information on saproxylic species ecology—and sometimes only large trees might be studied, rather than real veterans. Although we already know that veteran trees are essential habitat for a range of saproxylic organisms, there are still gaps in our knowledge of the specific conditions that veteran trees provide. It is vital that these are quantified and understood so that this information can be used to conserve veteran trees and their associated species.     

Simplified Aeroelastic Model for Fluid Structure Interaction between Microcantilever Sensors and Fluid Surroundings

Fluid-structural coupling occurs when microcantilever sensors vibrate in a fluid. Due to the complexity of the mechanical characteristics of microcantilevers and lack of high-precision microscopic mechanical testing instruments, effective methods for studying the fluid-structural coupling of microcantilevers are lacking, especially for non-rectangular microcantilevers. Here, we report fluid-structure interactions (FSI) of the cable-membrane structure via a macroscopic study. The simplified aeroelastic model was introduced into the microscopic field to establish a fluid-structure coupling vibration model for microcantilever sensors. We used the finite element method to solve the coupled FSI system. Based on the simplified aeroelastic model, simulation analysis of the effects of the air environment on the vibration of the commonly used rectangular microcantilever was also performed. The obtained results are consistent with the literature. The proposed model can also be applied to the auxiliary design of rectangular and non-rectangular sensors used in fluid environments.     

Morpho-anatomical and physiological responses to waterlogging stress in different barley (<Emphasis Type="Italic">Hordeum vulgare</Emphasis> L.) genotypes

Waterlogging is one of the major stresses limiting crop production worldwide. The understanding of the mechanisms of plant adaptations to waterlogging stress helps improve plant tolerance to stress. In this study, physiological responses and morpho-anatomical adaptations of seven different barley genotypes were investigated under waterlogging stress. The results showed that the waterlogging-tolerant varieties (TX9425, Yerong, TF58) showed less reduction in plant height, SPAD (soil–plant analyses development analyses) value, tillers, shoot and root biomasses than did the waterlogging-sensitive varieties (Franklin, Naso Nijo, TF57). Under waterlogging stress condition, the tolerant genotypes also showed a much larger number of adventitious roots than did the sensitive genotypes. More intercellular spaces and better integrated chloroplast membrane structures were observed in the leaves of the waterlogging-tolerant cultivars, which is likely due to increased ethylene content, decreased ABA content and less accumulation of O₂^.?. The ability to form new adventitious roots and intercellular spaces in shoots can also be used as selection criteria in breeding barley for waterlogging tolerance.     

Roles of Peroxisome Proliferator-Activated Receptor Gamma on Brain and Peripheral Inflammation

Peroxisome proliferator-activated receptor gamma (PPARγ) has been implicated in the pathology of numerous diseases involving diabetes, stroke, cancer, or obesity. It is expressed in diverse cell types, including vessels, immune and glial cells, and neurons. PPARγ plays crucial roles in the regulation of cellular differentiation, lipid metabolism, or glucose homeostasis. PPARγ ligands also exert effects on attenuating degenerative processes in the brain, as well as in peripheral systems, and it has been associated with the control of anti-inflammatory mechanisms, oxidative stress, neuronal death, neurogenesis, differentiation, and angiogenesis. This review will highlight key advances in the understanding of the PPARγ-related mechanisms responsible for neuroprotection after brain injuries, both ischemia and traumatic brain injury, and it will also cover the natural and synthetic agonist for PPARγ, angiotensin receptor blockers, and PPARγ antagonists, used in experimental and clinical research. A better understanding of the pleiotropic mechanisms and applications of these drugs to improve the recovery and to repair the acute and chronic induced neuroinflammation after brain injuries will pave the way for more effective therapeutic strategies after brain deficits.     

Bayesian nonparametric inference for panel count data with an informative observation process

In this paper, the panel count data analysis for recurrent events is considered. Such analysis is useful for studying tumor or infection recurrences in both clinical trial and observational studies. A bivariate Gaussian Cox process model is proposed to jointly model the observation process and the recurrent event process. Bayesian nonparametric inference is proposed for simultaneously estimating regression parameters, bivariate frailty effects, and baseline intensity functions. Inference is done through Markov chain Monte Carlo, with fully developed computational techniques. Predictive inference is also discussed under the Bayesian setting. The proposed method is shown to be efficient via simulation studies. A clinical trial dataset on skin cancer patients is analyzed to illustrate the proposed approach.     

Duration-dependent effects of nicotine exposure on growth and AKT activation in human kidney epithelial cells

Exposure to nicotine is known to cause adverse effects in many target organs including kidney. Epidemiological studies suggest that nicotine-induced kidney diseases are prevalent worldwide. However, the impact of duration of exposure on the nicotine-induced adverse effects in normal kidney cells and the underlying molecular mechanism is still unclear. Hence, the objective of this study was to evaluate both acute and long-term effects of nicotine in normal human kidney epithelial cells (HK-2). Cells were treated with 1 and 10 µM nicotine for acute and long-term duration. The result of cell viability showed that the acute exposure to 1 µM nicotine has no significant effect on growth. However, the 10 µM nicotine caused significant decrease in the growth of HK-2 cells. The long-term exposure resulted in significantly increased cell growth in both 1 and 10 µM nicotine-treated groups. Analysis of cell cycle and expression of marker genes related to proliferation and apoptosis further confirmed the effects of nicotine. Additionally, the analysis of growth signaling pathway revealed the decreased level of pAKT in cells with acute exposure whereas the increased level of pAKT in long-term nicotine-exposed cells. This suggests that nicotine, through modulating the AKT pathway, controls the duration-dependent effects on the growth of HK-2 cells. In summary, this is the first report showing long-duration exposure to nicotine causes increased proliferation of human kidney epithelial cells through activation of AKT pathway.     

EEG Spectral Analysis on OM Mantra Meditation: A Pilot Study

Mantra meditation is easy to practice. “OM” Mantra is the highest sacred symbol in Hinduism. The present study investigated the temporal dynamics of oscillatory changes after OM mantra meditation. Twenty-three naive meditators were asked to perform loud OM chanting for 30 min and the EEG were subsequently recorded with closed eyes before and after it. To obtain new insights into the nature of the EEG after OM chanting, EEG signals were analyzed using spectral domain analysis. Statistical analysis was performed using repeated measures of analysis of variance. It did not reveal any specific band involvement into OM mantra meditation. But significantly increase in theta power was found after meditation when averaged across all brain regions. This is the main effect of OM mantra meditation. However, the theta power showed higher theta amplitude after condition at all regions in comparison to the before condition of meditation. Finding was similar to other studies documenting reduction in cortical arousal during a state of relaxation. The study argues for the potential role of loud ‘OM’ chanting in offering relaxation. It provides a new perspective of meditation to the naive meditators. This information may help to demystify meditation and encourage those considering this as beneficial practice.