Merrittalbertsen0494

Understanding the processes underlying development and persistence of polarised opinions has been one of the key challenges in social networks for more than two decades. While plausible mechanisms have been suggested, they assume quite specialised interactions between individuals or groups that may only be relevant in particular contexts. We propose that a more broadly relevant explanation might be associated with the influence of external events. An agent-based bounded-confidence model has been used to demonstrate persistent polarisation of opinions within populations exposed to stochastic events (of positive and negative influence) even when all interactions between individuals are noisy and assimilative. Events can have a large impact on the distribution of opinions because their influence acts synchronistically across a large proportion of the population, whereas an individual can only interact with small numbers of other individuals at any particular time.This study aimed to investigate the contribution of renal dysfunction to enhanced hyperuricemia prevalence in older people. A cohort of 13,288 Chinese people aged between 40 and 95 years were recruited from January to May 2019. Serum uric acid concentration and estimated glomerular filtration rate [eGFR] were measured. The associations between age or eGFR and serum uric acid or hyperuricemia were analyzed using linear or binary logistic regression adjusting for risk factors. Uric acid concentration and prevalence of hyperuricemia were greater in older participants. Adjustment for reduced renal function (eGFR  less then  60 mL/min/1.73 m2) eliminated the associations between older age and higher uric acid concentration and between older age and higher prevalence of hyperuricemia diagnosis, whereas adjustment for other risk factors did not change those associations. Lower eGFR was associated with higher uric acid concentration both before (β = - 0.296, P  less then  0.001) and after adjustment for age (β = - 0.313, P  less then  0.001). Reduced renal function was associated with hyperuricemia diagnosis both before (odds ratio, OR, 3.64; 95% CI 3.10-4.28; P  less then  0.001) and after adjustment for age (adjusted OR, 3.82; 95% CI 3.22-4.54; P  less then  0.001). Mean serum uric acid and prevalence of hyperuricemia were higher in people with eGFR  less then  60 mL/min/1.73 m2 than those with eGFR ≥ 60 mL/min/1.73 m2. The prevalence of reduced renal function increased with older age (P  less then  0.001). This study suggests that reduced renal function can explain the increased uric acid levels and hyperuricemia diagnoses in older people.Autophagy is a lysosomal protein degradation system in which the cell self-digests its intracellular protein components and organelles. Defects in autophagy contribute to the pathogenesis of age-related chronic diseases, such as myocardial infarction and rheumatoid arthritis, through defects in the extracellular matrix (ECM). However, little is known about autophagy in periodontal diseases characterised by the breakdown of periodontal tissue. Tooth-supportive periodontal ligament (PDL) tissue contains PDL cells that produce various ECM proteins such as collagen to maintain homeostasis in periodontal tissue. In this study, we aimed to clarify the physiological role of autophagy in periodontal tissue. We found that autophagy regulated type I collagen synthesis by elimination of misfolded proteins in human PDL (HPDL) cells. Inhibition of autophagy by E-64d and pepstatin A (PSA) or siATG5 treatment suppressed collagen production in HPDL cells at mRNA and protein levels. Immunoelectron microscopy revealed collagen fragments in autolysosomes. Accumulation of misfolded collagen in HPDL cells was confirmed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis. E-64d and PSA treatment suppressed and rapamycin treatment accelerated the hard tissue-forming ability of HPDL cells. Our findings suggest that autophagy is a crucial regulatory process that facilitates type I collagen synthesis and partly regulates osteoblastic differentiation of PDL cells.Wrist rehabilitation is needed to help post-stroke and post-surgery patients recover from wrist fracture or injury. Traditional rehabilitation training is conducted by a therapist in a hospital, which hinders timely treatment due to the corresponding time and space constraints. This paper presents the design and implementation of a soft parallel robot for automated wrist rehabilitation. The presented wrist rehabilitation robot integrates the advantages of both soft robot and parallel robot structures. Unlike traditional rigid-body based rehabilitation robots, this soft parallel robot exhibits a compact structure, which is highly secure, adaptable, and flexible and thus a low-cost solution for personalized treatment. The proposed soft wrist-rehabilitation robot is driven by six evenly distributed linear actuators using pneumatic artificial muscles and one central linear electric motor. The introduced parallel-kinematic mechanism design enables the enhancement of the output stiffness of the soft robot for practical use. An electromyography sensor is adopted to provide feedback signals for evaluating the rehabilitation training process. A kinematic model of the designed robot is derived, and a prototype is fabricated for experimental testing. The results demonstrate that the developed soft rehabilitation robot can assist the wrist to realize all the required training motions, including abduction-adduction, flexion-extension, and supination-pronation. The compact and lightweight structure of this novel robot makes it convenient to use, and suitable rehabilitation training modes can be chosen for tailored rehabilitation at home or in a hospital.Filamentous fungi grow exclusively at their tips, where many growth-related fungal processes, such as enzyme secretion and invasion into host cells, take place. Hyphal tips are also a site of active metabolism. Understanding metabolic dynamics within the tip region is therefore important for biotechnology and medicine as well as for microbiology and ecology. However, methods that can track metabolic dynamics with sufficient spatial resolution and in a nondestructive manner are highly limited. Here we present time-lapse Raman imaging using a deuterium (D) tracer to study spatiotemporally varying metabolic activity within the hyphal tip of Aspergillus nidulans. By analyzing the carbon-deuterium (C-D) stretching Raman band with spectral deconvolution, we visualize glucose accumulation along the inner edge of the hyphal tip and synthesis of new proteins from the taken-up D-labeled glucose specifically at the central part of the apical region. find more Our results show that deuterium-labeled Raman imaging offers a broadly applicable platform for the study of metabolic dynamics in filamentous fungi and other relevant microorganisms in vivo.The isolation and sequencing of new strains of Pseudomonas aeruginosa created an extensive dataset of closed genomes. Many of the publicly available genomes are only used in their original publication while additional in silico information, based on comparison to previously published genomes, is not being explored. In this study, we defined and investigated the genome of the environmental isolate P. aeruginosa KRP1 and compared it to more than 100 publicly available closed P. aeruginosa genomes. By using different genomic island prediction programs, we could identify a total of 17 genomic islands and 8 genomic islets, marking the majority of the accessory genome that covers ~ 12% of the total genome. Based on intra-strain comparisons, we are able to predict the pathogenic potential of this environmental isolate. It shares a substantial amount of genomic information with the highly virulent PSE9 and LESB58 strains. For both of these, the increased virulence has been directly linked to their accessory genome before. Hence, the integrated use of previously published data can help to minimize expensive and time consuming wetlab work to determine the pathogenetic potential.Adoption of novel host plants by herbivorous insects can require new adaptations and may entail loss of adaptation to ancestral hosts. We examined relationships between an endangered subspecies of the butterfly Euphydryas editha (Taylor's checkerspot) and three host plant species. Two of the hosts (Castilleja hispida, Castilleja levisecta) were used ancestrally while the other, Plantago lanceolata, is exotic and was adopted more recently. We measured oviposition preference, neonate preference, larval growth, and secondary chemical uptake on all three hosts. Adult females readily laid eggs on all hosts but favored Plantago and tended to avoid C. levisecta. Oviposition preference changed over time. Neonates had no preference among host species, but consistently chose bracts over leaves within both Castilleja species. Larvae developed successfully on all species and grew to similar size on all of them unless they ate only Castilleja leaves (rather than bracts) which limited their growth. Diet strongly influenced secondary chemical uptake by larvae. Larvae that ate Plantago or C. hispida leaves contained the highest concentrations of iridoid glycosides, and iridoid glycoside composition varied with host species and tissue type. Despite having largely switched to a novel exotic host and generally performing better on it, this population has retained breadth in preference and ability to use other hosts.Human decision-making is subject to the biological limits of cognition. The fluidity of information propagation over online social media often leads users to experience information overload. This in turn affects which information received by users are processed and gain a response to, imposing constraints on volumes of, and participation in, information cascades. In this study, we investigate properties contributing to the visibility of online social media notifications by highly active users experiencing information overload via cross-platform social influence. We analyze simulations of a coupled agent-based model of information overload and the multi-action cascade model of conversation with evolutionary model discovery. Evolutionary model discovery automates mechanistic inference on agent-based models by enabling random forest importance analysis on genetically programmed agent-based model rules. The mechanisms of information overload have shown to contribute to a multitude of global properties of online information cascades. We investigate nine characteristics of online messages that may contribute to the prioritization of messages for response. Our results indicate that recency had the largest contribution to message visibility, with individuals prioritizing more recent notifications. Global popularity of the conversation originator had the second highest contribution, and reduced message visibility. Messages that presented opportunity for novel user interaction, yet high reciprocity showed to have relatively moderate contribution to message visibility. Finally, insights from the evolutionary model discovery results helped inform response prioritization rules, which improved the robustness and accuracy of the model of information overload.