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- Creators: College of Health Solutions
- Resource Type: Text
- Status: Published
The relationship between the neurobiology of speech and music has been investigated for more than a century. There remains no widespread agreement regarding how (or to what extent) music perception utilizes the neural circuitry that is engaged in speech processing, particularly at the cortical level. Prominent models such as Patel's Shared Syntactic Integration Resource Hypothesis (SSIRH) and Koelsch's neurocognitive model of music perception suggest a high degree of overlap, particularly in the frontal lobe, but also perhaps more distinct representations in the temporal lobe with hemispheric asymmetries. The present meta-analysis study used activation likelihood estimate analyses to identify the brain regions consistently activated for music as compared to speech across the functional neuroimaging (fMRI and PET) literature. Eighty music and 91 speech neuroimaging studies of healthy adult control subjects were analyzed. Peak activations reported in the music and speech studies were divided into four paradigm categories: passive listening, discrimination tasks, error/anomaly detection tasks and memory-related tasks. We then compared activation likelihood estimates within each category for music vs. speech, and each music condition with passive listening. We found that listening to music and to speech preferentially activate distinct temporo-parietal bilateral cortical networks. We also found music and speech to have shared resources in the left pars opercularis but speech-specific resources in the left pars triangularis. The extent to which music recruited speech-activated frontal resources was modulated by task. While there are certainly limitations to meta-analysis techniques particularly regarding sensitivity, this work suggests that the extent of shared resources between speech and music may be task-dependent and highlights the need to consider how task effects may be affecting conclusions regarding the neurobiology of speech and music.
Two distinct monocyte (Mo)/macrophage (Mp) subsets (Ly6Clow and Ly6Chi) orchestrate cardiac recovery process following myocardial infarction (MI). Prostaglandin (PG) E2 is involved in the Mo/Mp-mediated inflammatory response, however, the role of its receptors in Mos/Mps in cardiac healing remains to be determined. Here we show that pharmacological inhibition or gene ablation of the Ep3 receptor in mice suppresses accumulation of Ly6Clow Mos/Mps in infarcted hearts. Ep3 deletion in Mos/Mps markedly attenuates healing after MI by reducing neovascularization in peri-infarct zones. Ep3 deficiency diminishes CX3C chemokine receptor 1 (CX3CR1) expression and vascular endothelial growth factor (VEGF) secretion in Mos/Mps by suppressing TGFβ1 signaling and subsequently inhibits Ly6Clow Mos/Mps migration and angiogenesis. Targeted overexpression of Ep3 receptors in Mos/Mps improves wound healing by enhancing angiogenesis. Thus, the PGE2/Ep3 axis promotes cardiac healing after MI by activating reparative Ly6Clow Mos/Mps, indicating that Ep3 receptor activation may be a promising therapeutic target for acute MI.
Women with breast cancer often experience weight gain during and after treatment, significantly increasing risk for recurrence as well as all-cause mortality. Based on a growing body of evidence, meditative movement practices may be effective for weight management. First, we describe the effects of stress on factors associated with weight gain for breast cancer survivors. Then, a model is proposed that utilizes existing evidence to suggest how meditative movement supports behavioral, psychological, and neurohormonal changes that may explain weight loss. Application of the model suggests how a novel “mindful-body-wisdom” approach may work to help reduce weight for this at-risk group.
Cancer is sometimes depicted as a reversion to single cell behavior in cells adapted to live in a multicellular assembly. If this is the case, one would expect that mutation in cancer disrupts functional mechanisms that suppress cell-level traits detrimental to multicellularity. Such mechanisms should have evolved with or after the emergence of multicellularity. This leads to two related, but distinct hypotheses: 1) Somatic mutations in cancer will occur in genes that are younger than the emergence of multicellularity (1000 million years [MY]); and 2) genes that are frequently mutated in cancer and whose mutations are functionally important for the emergence of the cancer phenotype evolved within the past 1000 million years, and thus would exhibit an age distribution that is skewed to younger genes. In order to investigate these hypotheses we estimated the evolutionary ages of all human genes and then studied the probability of mutation and their biological function in relation to their age and genomic location for both normal germline and cancer contexts.
We observed that under a model of uniform random mutation across the genome, controlled for gene size, genes less than 500 MY were more frequently mutated in both cases. Paradoxically, causal genes, defined in the COSMIC Cancer Gene Census, were depleted in this age group. When we used functional enrichment analysis to explain this unexpected result we discovered that COSMIC genes with recessive disease phenotypes were enriched for DNA repair and cell cycle control. The non-mutated genes in these pathways are orthologous to those underlying stress-induced mutation in bacteria, which results in the clustering of single nucleotide variations. COSMIC genes were less common in regions where the probability of observing mutational clusters is high, although they are approximately 2-fold more likely to harbor mutational clusters compared to other human genes. Our results suggest this ancient mutational response to stress that evolved among prokaryotes was co-opted to maintain diversity in the germline and immune system, while the original phenotype is restored in cancer. Reversion to a stress-induced mutational response is a hallmark of cancer that allows for effectively searching “protected” genome space where genes causally implicated in cancer are located and underlies the high adaptive potential and concomitant therapeutic resistance that is characteristic of cancer.
The aim of this study was to investigate the potential associations of reallocating 30 minutes sedentary time in long bouts (>60 min) to sedentary time in non-bouts, light intensity physical activity (LPA) and moderate- to vigorous physical activity (MVPA) with cardiometabolic risk factors in a population diagnosed with prediabetes or type 2 diabetes.
Methods
Participants diagnosed with prediabetes and type 2 diabetes (n = 124, 50% men, mean [SD] age = 63.8 [7.5] years) were recruited to the physical activity intervention Sophia Step Study. For this study baseline data was used with a cross-sectional design. Time spent in sedentary behaviors in bouts (>60 min) and non-bouts (accrued in <60 min bouts) and physical activity was measured using the ActiGraph GT1M. Associations of reallocating bouted sedentary time to non-bouted sedentary time, LPA and MVPA with cardiometabolic risk factors were examined using an isotemporal substitution framework with linear regression models.
Results
Reallocating 30 minutes sedentary time in bouts to MVPA was associated with lower waist circumference (b = -4.30 95% CI:-7.23, -1.38 cm), lower BMI (b = -1.46 95% CI:-2.60, -0.33 kg/m2) and higher HDL cholesterol levels (b = 0.11 95% CI: 0.02, 0.21 kg/m[superscript 2]. Similar associations were seen for reallocation of sedentary time in non-bouts to MVPA. Reallocating sedentary time in bouts to LPA was associated only with lower waist circumference.
Conclusion
Reallocation of sedentary time in bouts as well as non-bouts to MVPA, but not to LPA, was beneficially associated with waist circumference, BMI and HDL cholesterol in individuals with prediabetes and type 2 diabetes. The results of this study confirm the importance of reallocation sedentary time to MVPA.
Limited research has examined how aspects of religion and spirituality can be incorporated into community-based physical activity programs delivered outside of religious institutions. The purpose of this study was to qualitatively explore how spirituality and religion can be leveraged in the design of community-based physical activity programs for African American women delivered outside of faith-based or faith-placed settings.
Results
Three focus groups were conducted were conducted with 23 African American women (M age = 37.8 years, M BMI = 39.6 kg m[superscript 2]). Results showed that incorporating aspects of spirituality (i.e., words encouraging connectedness to a higher power, meditation, mind–body activities) into a physical activity program was universally accepted among participants, regardless of religious affiliation. In contrast, including concepts of religion (i.e., bible verses and/or quotes from religious leaders) was controversial and not recommended among women who did not identify with a religious faith. Findings indicate that when developing community-based physical activity interventions that will not be delivered through faith-based or faith-placed settings, researchers should avoid references to specific religious beliefs. Instead, interventions should focus on spirituality and emphasize the mind–body relationship between physical activity and an African American women’s inner-being and her connectedness with a higher power.
Physical activity prevents or delays progression of impaired glucose tolerance in high-risk individuals. Physical activity promotion should serve as a basis in diabetes care. It is necessary to develop and evaluate health-promoting methods that are feasible as well as cost-effective within diabetes care. The aim of Sophia Step Study is to evaluate the impact of a multi-component and a single component physical activity intervention aiming at improving HbA[subscript 1c] (primary outcome) and other metabolic and cardiovascular risk factors, physical activity levels and overall health in patients with pre- and type 2 diabetes.
Methods/design
Sophia Step Study is a randomized controlled trial and participants are randomly assigned to either a multi-component intervention group (A), a pedometer group (B) or a control group (C). In total, 310 patients will be included and followed for 24 months. Group A participants are offered pedometers and a website to register steps, physical activity on prescription with yearly follow-ups, motivational interviewing (10 occasions) and group consultations (including walks, 12 occasions). Group B participants are offered pedometers and a website to register steps. Group C are offered usual care. The theoretical framework underpinning the interventions is the Health Belief Model, the Stages of Change Model, and the Social Cognitive Theory. Both the multi-component intervention (group A) and the pedometer intervention (group B) are using several techniques for behavior change such as self-monitoring, goal setting, feedback and relapse prevention.
Measurements are made at week 0, 8, 12, 16, month 6, 9, 12, 18 and 24, including metabolic and cardiovascular biomarkers (HbA[subscript 1c] as primary health outcome), accelerometry and daily steps. Furthermore, questionnaires were used to evaluate dietary intake, physical activity, perceived ability to perform physical activity, perceived support for being active, quality of life, anxiety, depression, well-being, perceived treatment, perceived stress and diabetes self- efficacy.
Discussion
This study will show if a multi-component intervention using pedometers with group- and individual consultations is more effective than a single- component intervention using pedometers alone, in increasing physical activity and improving HbA[subscript 1c], other metabolic and cardiovascular risk factors, physical activity levels and overall health in patients with pre- and type 2 diabetes.
Modeling of transcriptional regulatory networks (TRNs) has been increasingly used to dissect the nature of gene regulation. Inference of regulatory relationships among transcription factors (TFs) and genes, especially among multiple TFs, is still challenging. In this study, we introduced an integrative method, LogicTRN, to decode TF–TF interactions that form TF logics in regulating target genes. By combining cis-regulatory logics and transcriptional kinetics into one single model framework, LogicTRN can naturally integrate dynamic gene expression data and TF-DNA-binding signals in order to identify the TF logics and to reconstruct the underlying TRNs. We evaluated the newly developed methodology using simulation, comparison and application studies, and the results not only show their consistence with existing knowledge, but also demonstrate its ability to accurately reconstruct TRNs in biological complex systems.