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The periosteal and endosteal surfaces of mature bone are densely innervated by sensory nerves expressing TrkA, the high-affinity receptor for nerve growth factor (NGF). In previous work, we demonstrated that administration of exogenous NGF significantly increased load-induced bone formation through the activation of Wnt signaling. However, the translational potential of NGF is limited by the induction of substantial mechanical and thermal hyperalgesia in mice and humans. Here, we tested the effect of gambogic amide (GA), a recently identified robust small molecule agonist for TrkA, on hyperalgesia and load-induced bone formation. Behavioral analysis was used to assess pain up to one week after axial forelimb compression. Contrary to our expectations, GA treatment was not associated with diminished use of the loaded forelimb or sensitivity to thermal stimulus. Furthermore, dynamic histomorphometry revealed a significant increase in relative periosteal bone formation rate as compared to vehicle treatment. Additting skeletal adaptation to mechanical forces without inducing hyperalgesia.
This study examined the joint associations of sleep patterns and physical activity (PA) with all-cause, cardiovascular disease (CVD), and cancer mortality.
A total of 341,248 adults (mean age = 39.7 years; men 48.3%) were included in the study, with a 15-year follow-up. Participants reported sleep duration and disturbances (difficulty falling asleep, easily awakened, or use of sleeping medication). Necrostatin 2 solubility dmso PA was classified into 4 levels <7.5, 7.5-14.9, 15-29.9, and ≥30 metabolic equivalent hours per week (MET-h/week). To understand the joint associations of sleep patterns and PA with mortality, Cox proportional hazard models were conducted, with exposure variables combining sleep duration/disturbances and PA.
Compared with the reference group (sleeping 6-8 h/day), individuals who slept >8 h/day had higher risk for all-cause mortality (hazard ratios (HR) = 1.307, 95% confidence interval (95%CI) 1.248-1.369), CVD mortality (HR = 1.298, 95%CI 1.165-1.445), and cancer mortality (HR = 1.128, 95%CI 1.042-1.220liminated these detrimental associations.Photodynamic therapy (PDT) is an established clinical treatment technology which utilizes excitation light of a specific wavelength to activate photosensitizers (PSs) to generate reactive oxygen species (ROS), which leads to cancer cell death. Over the past decades of PDT research, progress have been made in the development of PSs. However, many inherent characteristics of traditional PSs have caused various problems in PDT, such as low treatment efficiency at aggregation state and shallow treatment depth. In solution to these problems, aggregation-induced emission (AIE)-based PSs have been reported in recent years. Here, this article reviews the design strategy and the biomedical applications of AIE PSs in detail, which begins with a summary of traditional PSs for a comparison between traditional PSs and AIE PSs. Subsequently, the different functional AIE PSs in photodynamic cancer cells ablation and image-guided therapy are discussed in detail taking controllable excitation wavelength, stimulus response and PDT/photothermal therapy synergistic effect as examples. These studies have demonstrated the great potential of AIE PSs as effective theranostic agents. And the review provides references for the development of new PSs and hopefully spur research interest in AIE PSs for future clinical application.Identifying mechanisms and pathways involved in gene-environment interplay and phenotypic plasticity is a long-standing challenge. It is highly desirable to establish an integrated framework with an environmental dimension for complex trait dissection and prediction. A critical step is to identify an environmental index that is both biologically relevant and estimable for new environments. With extensive field-observed complex traits, environmental profiles, and genome-wide single nucleotide polymorphisms for three major crops (maize, wheat, and oat), we demonstrated that identifying such an environmental index (i.e., a combination of environmental parameter and growth window) enables genome-wide association studies and genomic selection of complex traits to be conducted with an explicit environmental dimension. Interestingly, genes identified for two reaction-norm parameters (i.e., intercept and slope) derived from flowering time values along the environmental index were less colocalized for a diverse maize panel than for wheat and oat breeding panels, agreeing with the different diversity levels and genetic constitutions of the panels. In addition, we showcased the usefulness of this framework for systematically forecasting the performance of diverse germplasm panels in new environments. This general framework and the companion CERIS-JGRA analytical package should facilitate biologically informed dissection of complex traits, enhanced performance prediction in breeding for future climates, and coordinated efforts to enrich our understanding of mechanisms underlying phenotypic variation.
Sex-based neurobiological heterogeneity in autism is poorly understood. Research is disproportionately biased to males, leading to an unwarranted presumption that autism neurobiology is the same across sexes. Previous neuroimaging studies using amalgamated multicenter datasets to increase autistic female samples are characterized by large statistical noise.
We used a better-powered dataset of 1183 scans of 839 individuals-299 (467 scans) autistic males, 74 (102 scans) autistic females, 240 (334 scans) control males, and 226 (280 scans) control females-to test two whole-brain models of overall/global sex modulations on autism neuroanatomy, by summary measures computed across the brain the local magnitude model, in which the same brain regions/circuitries are involved across sexes but effect sizes are larger in females, indicating quantitative sex modulation; and spatial dissimilarity model, in which the neuroanatomy differs spatially between sexes, indicating qualitative sex modulation. The male and female autism groups were matched on age, IQ, and autism symptoms.
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