Prioritization of Epilepsy Associated Candidate Genes by Convergent Analysis

Epilepsy is a severe neurological disorder affecting a large number of individuals, yet the underlying genetic risk factors for epilepsy remain unclear. Recent studies have revealed several recurrent copy number variations (CNVs) that are more likely to be associated with epilepsy. The responsible gene(s) within these regions have yet to be definitively linked to the disorder, and the implications of their interactions are not fully understood. Identification of these genes may contribute to a better pathological understanding of epilepsy, and serve to implicate novel therapeutic targets for further research.In this study, we examined genes within heterozygous deletion regions identified in a recent large-scale study, encompassing a diverse spectrum of epileptic syndromes. By integrating additional protein-protein interaction data, we constructed subnetworks for these CNV-region genes and also those previously studied for epilepsy. We observed 20 genes common to both networks, primarily concentrated within a small molecular network populated by GABA receptor, BDNF/MAPK signaling, and estrogen receptor genes. From among the hundreds of genes in the initial networks, these were designated by convergent evidence for their likely association with epilepsy. Importantly, the identified molecular network was found to contain complex interrelationships, providing further insight into epilepsy's underlying pathology. We further performed pathway enrichment and crosstalk analysis and revealed a functional map which indicates the significant enrichment of closely related neurological, immune, and kinase regulatory pathways.The convergent framework we proposed here provides a unique and powerful approach to screening and identifying promising disease genes out of typically hundreds to thousands of genes in disease-related CNV-regions. Our network and pathway analysis provides important implications for the underlying molecular mechanisms for epilepsy. The strategy can be applied for the study of other complex diseases

Avian Pathogenic Escherichia coli (APEC) Infection Alters Bone Marrow Transcriptome in Chickens

Avian pathogenic Escherichia coli (APEC) is a major cause of disease impacting animal health. The bone marrow is the reservoir of immature immune cells; however, it has not been examined to date for gene expression related to developmental changes (cell differentiation, maturation, programming) after APEC infection. Here, we study gene expression in the bone marrow between infected and non-infected animals, and between infected animals with mild (resistant) versus severe (susceptible) pathology, at two times post-infection. We sequenced 24 bone marrow RNA libraries generated from the six different treatment groups with four replicates each, and obtained an average of 22 million single-end, 100-bp reads per library. Genes were detected as differentially expressed (DE) between APEC treatments (mild pathology, severe pathology, and mock-challenged) at a given time point, or DE between 1 and 5 days post-infection (dpi) within the same treatment group. Results demonstrate that many immune cells, genes and related pathways are key contributors to the different responses to APEC infection between susceptible and resistant birds and between susceptible and non-challenged birds, at both times post-infection. In susceptible birds, lymphocyte differentiation, proliferation, and maturation were greatly impaired, while the innate and adaptive immune responses, including dendritic cells, monocytes and killer cell activity, TLR- and NOD-like receptor signaling, as well as T helper cells and many cytokine activities, were markedly enhanced. The resistant birds’ immune system, however, was similar to that of non-challenged birds. The DE genes in the immune cells and identified signaling models are representative of activation and resolution of infection in susceptible birds at both post-infection days. These novel results characterizing transcriptomic response to APEC infection reveal that there is combinatorial activity of multiple genes controlling myeloid cells, and B and T cell lymphopoiesis, as well as immune responses occurring in the bone marrow in these early stages of response to infection

Overconfidence in Labor Markets

This chapter reviews how worker overconfidence affects labor markets. Evidence from psychology and economics shows that in many situations, most people tend to overestimate their absolute skills, overplace themselves relative to others, and overestimate the precision of their knowledge. The chapter starts by reviewing evidence for overconfidence and for how overconfidence affects economic choices. Next, it reviews economic explanations for overconfidence. After that, it discusses research on the impact of worker overconfidence on labor markets where wages are determined by bargaining between workers and firms. Here, three key questions are addressed. First, how does worker overconfidence affect effort provision for a fixed compensation scheme? Second, how should firms design compensation schemes when workers are overconfident? In particular, will a compensation scheme offered to an overconfident worker have higher-or lower-powered incentives than that offered to a worker with accurate self-perception? Third, can worker overconfidence lead to a Pareto improvement? The chapter continues by reviewing research on the impact of worker overconfidence on labor markets where workers can move between firms and where neither firms nor workers have discretion over wage setting. The chapter concludes with a summary of its main findings and a discussion of avenues for future research

Biomechanical considerations in the pathogenesis of osteoarthritis of the knee

Osteoarthritis is the most common joint disease and a major cause of disability. The knee is the large joint most affected. While chronological age is the single most important risk factor of osteoarthritis, the pathogenesis of knee osteoarthritis in the young patient is predominantly related to an unfavorable biomechanical environment at the joint. This results in mechanical demand that exceeds the ability of a joint to repair and maintain itself, predisposing the articular cartilage to premature degeneration. This review examines the available basic science, preclinical and clinical evidence regarding several such unfavorable biomechanical conditions about the knee: malalignment, loss of meniscal tissue, cartilage defects and joint instability or laxity

Data accompanying Milodowski et al. (Journal of Applied Ecology, 2021): "The impact of logging on vertical canopy structure across a gradient of tropical forest degradation intensity in Borneo"

Description: LiDAR point cloud data: LiDAR point clouds for the GEM inventory plots across SAFE, Maliau Conservation Area and Danum Valley in Malaysian Borneo. The georeferenced point clouds were produced following a survey by the Natural Environment Research Council Airborne Research Facility in 2014, noise points were removed and ground points classified using Lastools. Digital terrain models (DTM) were produced from classified ground points at 10 m resolution. Point clouds were normalised (through ground subtraction) to produce point heights relative to the local ground elevation. Crown surveys: In each plot, the positions and heights of all trees with a stem diameter at breast height (DBH) ≥ 10 cm were mapped using ground-based Field-Map technology (IFER, Ltd., Jílové u Prahy, Czech Republic) in 2016. We mapped individual tree crowns by measuring 5-30 spatial positions, representing the boundary of a crown projected onto the horizontal plane. Crown projections were smoothed using the "smooth contour line" feature of Field-Map software v.11. Small stem inventories: At SAFE and Maliau Basin, DBH was measured for all stems >2 cm for 4-5 of the subplots in each GEM plot in 2012-2013 (in the manuscript, we used the average stem size distributions to estimate canopy volume contributions for the un-surveyed subplots). At the Danum Valley sites, DBH was measured for all subplots in a stem census comprising all stems >1 cm in 2011=2012 (DAN-04) and 2013-2014 (DAN-05), as part of the ForestGEO 50 ha inventory plot. Full data from Danum Valley is available, subject to conditions of usage, from the ForestGEO data portal: http://ctfs.si.edu/datarequest/

Responses of tropical bats to habitat fragmentation, logging, and deforestation

Land-use change is a key driver of the global biodiversity crisis and a particularly serious threat to tropical biodiversity. Throughout the tropics, the staggering pace of deforestation, logging, and conversion of forested habitat to other land uses has created highly fragmented landscapes that are increasingly dominated by human-modified habitats and degraded forests. In this chapter, we review the responses of tropical bats to a range of land-use change scenarios, focusing on the effects of habitat fragmentation, logging, and conversion of tropical forest to various forms of agricultural production. Recent landscape- scale studies have considerably advanced our understanding of how tropical bats respond to habitat fragmentation and disturbance at the population, ensemble and assemblage level. This research emphasizes that responses of bats are often species- and ensemble-specific, sensitive to spatial scale, and strongly molded by the characteristics of the prevailing landscape matrix. Nonetheless, substantial knowledge gaps exist concerning other types of response by bats. Few studies have assessed responses at the genetic, behavioral or physiological level, with regard to disease prevalence, or the extent to which human disturbance erodes the capacity of tropical bats to provide key ecosystem services. A strong geographical bias, with Asia and, most notably, Africa, being strongly understudied, precludes a comprehensive understanding of the effects of fragmentation and disturbance on tropical bats. We strongly encourage increased research in the Paleotropics, and emphasize the need for long-term studies, approaches designed to integrate multiple scales, and answering questions that are key to conserving tropical bats in an era of environmental change and dominance of modified habitats (i.e., the Anthropocene)

Resting-state global functional connectivity as a biomarker of cognitive reserve in mild cognitive impairment

Cognitive reserve (CR) shows protective effects in Alzheimer’s disease (AD) and reduces the risk of dementia. Despite the clinical significance of CR, a clinically useful diagnostic biomarker of brain changes underlying CR in AD is not available yet. Our aim was to develop a fully-automated approach applied to fMRI to produce a biomarker associated with CR in subjects at increased risk of AD. We computed resting-state global functional connectivity (GFC), i.e. the average connectivity strength, for each voxel within the cognitive control network, which may sustain CR due to its central role in higher cognitive function. In a training sample including 43 mild cognitive impairment (MCI) subjects and 24 healthy controls (HC), we found that MCI subjects with high CR (> median of years of education, CR+) showed increased frequency of high GFC values compared to MCI-CR- and HC. A summary index capturing such a surplus frequency of high GFC was computed (called GFC reserve (GFC-R) index). GFC-R discriminated MCI-CR+ vs. MCI-CR-, with the area under the ROC = 0.84. Cross-validation in an independently recruited test sample of 23 MCI subjects showed that higher levels of the GFC-R index predicted higher years of education and an alternative questionnaire-based proxy of CR, controlled for memory performance, gray matter of the cognitive control network, white matter hyperintensities, age, and gender. In conclusion, the GFC-R index that captures GFC changes within the cognitive control network provides a biomarker candidate of functional brain changes of CR in patients at increased risk of AD