The influence of α-actinin-3 deficiency on bone remodelling markers in young men

There is a large individual variation in the bone remodelling markers (BRMs) osteocalcin (OC), procollagen 1 N-terminal propeptide (P1NP) and β-isomerized C-terminal telopeptide (β-CTx), as well as undercarboxylated osteocalcin (ucOC), at rest and in response to exercise. α-actinin-3 (ACTN3), a sarcomeric protein, is expressed in skeletal muscle and osteoblasts and may influence BRM levels and the cross-talk between muscle and bone. We tested the levels of serum BRMs in α-actinin-3 deficient humans (ACTN3 XX) at baseline, and following a single bout of exercise. Forty-three healthy Caucasian individuals were divided into three groups (ACTN3 XX, n = 13; ACTN3 RX, n = 16; ACTN3 RR, n = 14). Participants completed a single session of High Intensity Interval Exercise (HIIE) on a cycle ergometer (8 × 2-min intervals at 85% of maximal power). Blood samples were taken before, immediately after, and three hours post exercise to identify the peak changes in serum BRMs. There was a stepwise increase in resting serum BRMs across the ACTN3 genotypes (XX \u3e RX \u3e RR) with significantly higher levels of tOC ~ 26%, P1NP ~ 34%, and β-CTX (~ 33%) in those with ACTN3 XX compared to ACTN3 RR. Following exercise BRMs and ucOC were higher in all three ACTN3 genotypes, with no significant differences between groups. Serum levels of tOC, P1NP and β-CTX are higher in men with ACTN3 XX genotype (α-actinin-3 deficiency) compared to RR and RX. It appears that the response of BRMs and ucOC to exercise is not explained by the ACTN3 genotype

The biomass burning contribution to climate-carbon-cycle feedback

Temperature exerts strong controls on the incidence and severity of fire. All else equal, warming is expected to increase fire-related carbon emissions, and thereby atmospheric CO2. But the magnitude of this feedback is very poorly known. We use a single-box model of the land biosphere to quantify this positive feedback from satellite-based estimates of biomass burning emissions for 2000–2014 CE and from sedimentary charcoal records for the millennium before the industrial period. We derive an estimate of the centennial-scale feedback strength of 6.5 ± 3.4 ppm CO2 per degree of land temperature increase, based on the satellite data. However, this estimate is poorly constrained, and is largely driven by the well-documented dependence of tropical deforestation and peat fires (primarily anthropogenic) on climate variability patterns linked to the El Niño–Southern Oscillation. Palaeo-data from pre-industrial times provide the opportunity to assess the fire-related climate–carbon-cycle feedback over a longer period, with less pervasive human impacts. Past biomass burning can be quantified based on variations in either the concentration and isotopic composition of methane in ice cores (with assumptions about the isotopic signatures of different methane sources) or the abundances of charcoal preserved in sediments, which reflect landscape-scale changes in burnt biomass. These two data sources are shown here to be coherent with one another. The more numerous data from sedimentary charcoal, expressed as normalized anomalies (fractional deviations from the long-term mean), are then used – together with an estimate of mean biomass burning derived from methane isotope data – to infer a feedback strength of 5.6 ± 3.2 ppm CO2 per degree of land temperature and (for a climate sensitivity of 2.8 K) a gain of 0.09 ± 0.05. This finding indicates that the positive carbon cycle feedback from increased fire provides a substantial contribution to the overall climate–carbon-cycle feedback on centennial timescales. Although the feedback estimates from palaeo- and satellite-era data are in agreement, this is likely fortuitous because of the pervasive influence of human activities on fire regimes during recent decades

A One Base Pair Deletion in the Canine ATP13A2 Gene Causes Exon Skipping and Late-Onset Neuronal Ceroid Lipofuscinosis in the Tibetan Terrier

Neuronal ceroid lipofuscinosis (NCL) is a progressive neurodegenerative disease characterized by brain and retinal atrophy and the intracellular accumulation of autofluorescent lysosomal storage bodies resembling lipofuscin in neurons and other cells. Tibetan terriers show a late-onset lethal form of NCL manifesting first visible signs at 5–7 years of age. Genome-wide association analyses for 12 Tibetan-terrier-NCL-cases and 7 Tibetan-terrier controls using the 127K canine Affymetrix SNP chip and mixed model analysis mapped NCL to dog chromosome (CFA) 2 at 83.71–84.72 Mb. Multipoint linkage and association analyses in 376 Tibetan terriers confirmed this genomic region on CFA2. A mutation analysis for 14 positional candidate genes in two NCL-cases and one control revealed a strongly associated single nucleotide polymorphism (SNP) in the MAPK PM20/PM21 gene and a perfectly with NCL associated single base pair deletion (c.1620delG) within exon 16 of the ATP13A2 gene. The c.1620delG mutation in ATP13A2 causes skipping of exon 16 presumably due to a broken exonic splicing enhancer motif. As a result of this mutation, ATP13A2 lacks 69 amino acids. All known 24 NCL cases were homozygous for this deletion and all obligate 35 NCL-carriers were heterozygous. In a sample of 144 dogs from eleven other breeds, the c.1620delG mutation could not be found. Knowledge of the causative mutation for late-onset NCL in Tibetan terrier allows genetic testing of these dogs to avoid matings of carrier animals. ATP13A2 mutations have been described in familial Parkinson syndrome (PARK9). Tibetan terriers with these mutations provide a valuable model for a PARK9-linked disease and possibly for manganese toxicity in synucleinopathies

Homeostatic Scaling of Excitability in Recurrent Neural Networks

Neurons adjust their intrinsic excitability when experiencing a persistent change in synaptic drive. This process can prevent neural activity from moving into either a quiescent state or a saturated state in the face of ongoing plasticity, and is thought to promote stability of the network in which neurons reside. However, most neurons are embedded in recurrent networks, which require a delicate balance between excitation and inhibition to maintain network stability. This balance could be disrupted when neurons independently adjust their intrinsic excitability. Here, we study the functioning of activity-dependent homeostatic scaling of intrinsic excitability (HSE) in a recurrent neural network. Using both simulations of a recurrent network consisting of excitatory and inhibitory neurons that implement HSE, and a mean-field description of adapting excitatory and inhibitory populations, we show that the stability of such adapting networks critically depends on the relationship between the adaptation time scales of both neuron populations. In a stable adapting network, HSE can keep all neurons functioning within their dynamic range, while the network is undergoing several (patho)physiologically relevant types of plasticity, such as persistent changes in external drive, changes in connection strengths, or the loss of inhibitory cells from the network. However, HSE cannot prevent the unstable network dynamics that result when, due to such plasticity, recurrent excitation in the network becomes too strong compared to feedback inhibition. This suggests that keeping a neural network in a stable and functional state requires the coordination of distinct homeostatic mechanisms that operate not only by adjusting neural excitability, but also by controlling network connectivity

No evidence of a common DNA variant profile specific to world class endurance athletes

There are strong genetic components to cardiorespiratory fitness and its response to exercise training. It would be useful to understand the differences in the genomic profile of highly trained endurance athletes of world class caliber and sedentary controls. An international consortium (GAMES) was established in order to compare elite endurance athletes and ethnicity-matched controls in a case-control study design. Genome-wide association studies were undertaken on two cohorts of elite endurance athletes and controls (GENATHLETE and Japanese endurance runners), from which a panel of 45 promising markers was identified. These markers were tested for replication in seven additional cohorts of endurance athletes and controls: from Australia, Ethiopia, Japan, Kenya, Poland, Russia and Spain. The study is based on a total of 1520 endurance athletes (835 who took part in endurance events in World Championships and/or Olympic Games) and 2760 controls. We hypothesized that world-class athletes are likely to be characterized by an even higher concentration of endurance performance alleles and we performed separate analyses on this subsample. The meta-analysis of all available studies revealed one statistically significant marker (rs558129 at GALNTL6 locus, p = 0.0002), even after correcting for multiple testing. As shown by the low heterogeneity index (I2 = 0), all eight cohorts showed the same direction of association with rs558129, even though p-values varied across the individual studies. In summary, this study did not identify a panel of genomic variants common to these elite endurance athlete groups. Since GAMES was underpowered to identify alleles with small effect sizes, some of the suggestive leads identified should be explored in expanded comparisons of world-class endurance athletes and sedentary controls and in tightly controlled exercise training studies. Such studies have the potential to illuminate the biology not only of world class endurance performance but also of compromised cardiac functions and cardiometabolic diseases

Dynamics of Dynamics within a Single Data Acquisition Session: Variation in Neocortical Alpha Oscillations in Human MEG

Background Behavioral paradigms applied during human recordings in electro- and magneto- encephalography (EEG and MEG) typically require 1–2 hours of data collection. Over this time scale, the natural fluctuations in brain state or rapid learning effects could impact measured signals, but are seldom analyzed. Methods and Findings We investigated within-session dynamics of neocortical alpha (7–14 Hz) rhythms and their allocation with cued-attention using MEG recorded from primary somatosensory neocortex (SI) in humans. We found that there were significant and systematic changes across a single ~1 hour recording session in several dimensions, including increased alpha power, increased differentiation in attention-induced alpha allocation, increased distinction in immediate time-locked post-cue evoked responses in SI to different visual cues, and enhanced power in the immediate cue-locked alpha band frequency response. Further, comparison of two commonly used baseline methods showed that conclusions on the evolution of alpha dynamics across a session were dependent on the normalization method used. Conclusions These findings are important not only as they relate to studies of oscillations in SI, they also provide a robust example of the type of dynamic changes in brain measures within a single session that are overlooked in most human brain imaging/recording studies.National Institutes of Health (U.S.) (P41RR14075)National Institutes of Health (U.S.) (K25MH072941)National Institutes of Health (U.S.) (K01AT003459)National Institutes of Health (U.S.) (1RO1-NS045130-01)National Institutes of Health (U.S.) (T32GM007484)National Science Foundation (U.S.) (0316933)Osher Lifelong Learning Institute

Assessment of the health of Americans: the average health-related quality of life and its inequality across individuals and groups

BACKGROUND: The assessment of population health has traditionally relied on the population's average health measured by mortality related indicators. Researchers have increasingly recognized the importance of including information on health inequality and health-related quality of life (HRQL) in the assessment of population health. The objective of this study is to assess the health of Americans in the 1990s by describing the average HRQL and its inequality across individuals and groups. METHODS: This study uses the 1990 and 1995 National Health Interview Survey from the United States. The measure of HRQL is the Health and Activity Limitation Index (HALex). The measure of health inequality across individuals is the Gini coefficient. This study provides confidence intervals (CI) for the Gini coefficient by a bootstrap method. To describe health inequality by group, this study decomposes the overall Gini coefficient into the between-group, within-group, and overlap Gini coefficient using race (White, Black, and other) as an example. This study looks at how much contribution the overlap Gini coefficient makes to the overall Gini coefficient, in addition to the absolute mean differences between groups. RESULTS: The average HALex was the same in 1990 (0.87, 95% CI: 0.87, 0.88) and 1995 (0.87, 95% CI: 0.86, 0.87). The Gini coefficient for the HALex distribution across individuals was greater in 1995 (0.097, 95% CI: 0.096, 0.099) than 1990 (0.092, 95% CI: 0.091, 0.094). Differences in the average HALex between all racial groups were the same in 1995 as 1990. The contribution of the overlap to the overall Gini coefficient was greater in 1995 than in 1990 by 2.4%. In both years, inequality between racial groups accounted only for 4–5% of overall inequality. CONCLUSION: The average HRQL of Americans was the same in 1990 and 1995, but inequality in HRQL across individuals was greater in 1995 than 1990. Inequality in HRQL by race was smaller in 1995 than 1990 because race had smaller effect on the way health was distributed in 1995 than 1990. Analysis of the average HRQL and its inequality provides information on the health of a population invisible in the traditional analysis of population health

No evidence of a common DNA variant profile specific to world class endurance athletes

There are strong genetic components to cardiorespiratory fitness and its response to exercise training. It would be useful to understand the differences in the genomic profile of highly trained endurance athletes of world class caliber and sedentary controls. An international consortium (GAMES) was established in order to compare elite endurance athletes and ethnicity- matched controls in a case-control study design. Genome-wide association studies were undertaken on two cohorts of elite endurance athletes and controls (GENATHLETE and Japanese endurance runners), from which a panel of 45 promising markers was identified. These markers were tested for replication in seven additional cohorts of endurance athletes and controls: from Australia, Ethiopia, Japan, Kenya, Poland, Russia and Spain. The study is based on a total of 1520 endurance athletes (835 who took part in endurance events in World Championships and/or Olympic Games) and 2760 controls. We hypothesized that world-class athletes are likely to be characterized by an even higher concentration of endurance performance alleles and we performed separate analyses on this subsample. The meta-analysis of all available studies revealed one statistically significant marker (rs558129 at GALNTL6 locus, p = 0.0002), even after correcting for multiple testing. As shown by the low heterogeneity index (I2 = 0), all eight cohorts showed the same direction of association with rs558129, even though p-values varied across the individual studies. In summary, this study did not identify a panel of genomic variants common to these elite endurance athlete groups. Since GAMES was underpowered to identify alleles with small effect sizes, some of the suggestive leads identified should be explored in expanded comparisons of world-class endurance athletes and sedentary controls and in tightly controlled exercise training studies. Such studies have the potential to illuminate the biology not only of world class endurance performance but also of compromised cardiac functions and cardiometabolic diseases