Centrosome misorientation reduces stem cell division during ageing

Asymmetric division of adult stem cells generates one self- renewing stem cell and one differentiating cell, thereby maintaining tissue homeostasis. A decline in stem cell function has been proposed to contribute to tissue ageing, although the underlying mechanism is poorly understood. Here we show that changes in the stem cell orientation with respect to the niche during ageing contribute to the decline in spermatogenesis in the male germ line of Drosophila. Throughout the cell cycle, centrosomes in germline stem cells ( GSCs) are oriented within their niche and this ensures asymmetric division. We found that GSCs containing misoriented centrosomes accumulate with age and that these GSCs are arrested or delayed in the cell cycle. The cell cycle arrest is transient, and GSCs appear to re- enter the cell cycle on correction of centrosome orientation. On the basis of these findings, we propose that cell cycle arrest associated with centrosome misorientation functions as a mechanism to ensure asymmetric stem cell division, and that the inability of stem cells to maintain correct orientation during ageing contributes to the decline in spermatogenesis. We also show that some of the misoriented GSCs probably originate from dedifferentiation of spermatogonia.University of Michigan ; March of Dimes Basil O'Conner Starter Scholar Research Award ; Searle Scholar Program ; NIH [P01 DK53074, R01GM072006]We thank C. Gonzalez, D. McKearin, N. Rusan, M. Peifer and the Bloomington Stock Center for fly stocks; R. Lehmann, C. Field and the Developmental Studies Hybridoma Bank for antibodies; M. Kiel and D. Nakada for help with X-ray irradiation; and S. Morrison and T. Mahowald for comments on the manuscript. This research was supported by a University of Michigan start-up fund, March of Dimes Basil O'Conner Starter Scholar Research Award and the Searle Scholar Program (to Y.M.Y.), and NIH grants P01 DK53074 (to M.T.F.) and R01GM072006 (to A.J.H.).Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62879/1/nature07386.pd

Functional analysis of Pro-inflammatory properties within the cerebrospinal fluid after subarachnoid hemorrhage in vivo and in vitro

<p>Abstract</p> <p>Background</p> <p>To functionally characterize pro-inflammatory and vasoconstrictive properties of cerebrospinal fluid after aneurysmal subarachnoid hemorrhage (SAH) in vivo and in vitro.</p> <p>Methods</p> <p>The cerebrospinal fluid (CSF) of 10 patients suffering from SAH was applied to the transparent skinfold chamber model in male NMRI mice which allows for in vivo analysis of the microcirculatory response to a superfusat. Microvascular diameter changes were quantified and the numbers of rolling and sticking leukocytes were documented using intravital multifluorescence imaging techniques. Furthermore, the pro-inflammatory properties of CSF were assessed in vitro using a monocyte transendothelial migration assay.</p> <p>Results</p> <p>CSF superfusion started to induce significant vasoconstriction on days 4 and 6 after SAH. In parallel, CSF superfusion induced a microvascular leukocyte recruitment, with a significant number of leukocytes rolling (day 6) and sticking (days 2-4) to the endothelium. CSF of patients presenting with cerebral edema induced breakdown of blood vessel integrity in our assay as evidenced by fluorescent marker extravasation. In accordance with leukocyte activation in vivo, significantly higher in vitro monocyte migration rates were found after SAH.</p> <p>Conclusion</p> <p>We functionally characterized inflammatory and vasoactive properties of patients' CSF after SAH in vivo and in vitro. This pro-inflammatory milieu in the subarachnoid space might play a pivotal role in the pathophysiology of early and delayed brain injury as well as vasospasm development following SAH.</p

Human Activity Recognition Based on Wavelet-Based Features along with Feature Prioritization

Activity recognition from human action data is quite a challenging task in the biomedical data science community. The main challenge in dealing with human activity recognition (HAR) datasets is their high cardinality. Therefore, reducing cardinality is a cardinal area of research in the HAR field. In this research, reducing the data dimensionality by utilizing future selection methods has been used. This research work has extracted features using wavelet packet transform (WPT) and the cardinality of the feature set has been reduced by using the Genetic Algorithm (GA) technique. The selected features also have been ranked according to their importance based on their SHAP values. In the venture, an interesting inspection has been found. That is in HAR datasets, signal values lay into lower frequency regions mostly. The highest accuracy and f1-score which have been got are 94.74%, 94.73%, and 89.98%, 89.67% for the feature extracted and feature selected dataset respectively

Improving Return on Investment for Photovoltaic Plants by Deploying Customized Load

&copy; 2020 IEEE. The deployment of grid connected photovoltaic (PV) power plants is increasing dramatically recently. Due to the intermittent nature of the PV power plant, a battery and/or a power curtailment controller has to be installed to maintain the stability of the distribution network. The battery is an additional cost in the system so the return on investment (ROI) analysis has to be conducted. An alternative to the battery, a customized load can be used to consume the surplus energy. This load has to make an additional income to be profitable for the plant\u27s owner. Such load can be crypto-currency mining rig that does calculation to validate the transaction in the Blockchain network. This study compared the ROI of the battery and the mining rig. The study shows that mining rig has higher ROI of 7.7% compared to 4.5% for battery

Hybrid AC/DC Microgrid Modelling for Affordable Rural Electrification

© 2020 IEEE. Uninterrupted and adequate electricity supply to the resident of rural areas is still a big challenge due to the shortage of national electricity production and a weak distribution system in many countries. Along with these issues, the current high Cost of Electricity (COE) is another hindrance of ensuring electricity for rural people. To mitigate this economic impediment along with addressing environmental issues, a microgrid (MG) could be a suitable solution. This work proposes a PV-Wind-Battery-Gas connected MG architecture that provides a reasonable level of CO2 emission in two differently located remote urban areas. Simulation results conclude that the proposed model can provide environment friendly as well as economical electrification