Sedentariness and Health: Is Sedentary Behavior More Than Just Physical Inactivity?

Sedentary behavior refers to certain activities in a reclining, seated, or lying position requiring very low energy expenditure. It has been suggested to be distinct from physical inactivity and an independent predictor of metabolic risk even if an individual meets current physical activity guidelines. Over the past decades, a shift in the activity profile of individuals has been observed with vigorous physical activity and sleep being partly replaced by cognitive work, a potential neurogenic stress component considering its hormonal and neurophysiological effects, leading to various impacts on health. Mental work, for instance, may significantly increase glycemic instability leading to an increase in the desire to eat and thus, higher energy intakes. Furthermore, screen-based leisure activities (e.g., television watching) and screen-based work activities (e.g., computer use for work purposes) have often been considered together while they may not trigger the same stress response and/or use of substrate. Thus, the problems of sedentariness may not only be attributed to a lack of movement, but also to the stimulation provided by replacing activities. The objective of this review is to discuss the (1) recent evidence and current state of knowledge regarding the health impact of sedentary behaviors on health; (2) potential neurogenic effects of cognitive work as a sedentary behavior; (3) link between sedentary behaviors and the diet; (4) resemblance between sedentary behaviors and the inadequate sleeper; and (5) potential solutions to reduce sedentary behaviors and increase physical activity

Synchronization in networked systems with large parameter heterogeneity

Systems that synchronize in nature are intrinsically different from one another, with possibly large differences from system to system. While a vast part of the literature has investigated the emergence of network synchronization for the case of small parametric mismatches, we consider the general case that parameter mismatches may be large. We present a unified stability analysis that predicts why the range of stability of the synchronous solution either increases or decreases with parameter heterogeneity for a given network. We introduce a parametric approach, based on the definition of a curvature contribution function, which allows us to estimate the effect of mismatches on the stability of the synchronous solution in terms of contributions of pairs of eigenvalues of the Laplacian. For cases in which synchronization occurs in a bounded interval of a parameter, we study the effects of parameter heterogeneity on both transitions (asynchronous to synchronous and synchronous to asynchronous.)Comment: Accepted for publication in Communications Physic

Rate-induced tipping in complex high-dimensional ecological networks

In an ecosystem, environmental changes as a result of natural and human processes can cause some key parameters of the system to change with time. Depending on how fast such a parameter changes, a tipping point can occur. Existing works on rate-induced tipping, or R-tipping, offered a theoretical way to study this phenomenon but from a local dynamical point of view, revealing, e.g., the existence of a critical rate for some specific initial condition above which a tipping point will occur. As ecosystems are subject to constant disturbances and can drift away from their equilibrium point, it is necessary to study R-tipping from a global perspective in terms of the initial conditions in the entire relevant phase space region. In particular, we introduce the notion of the probability of R-tipping defined for initial conditions taken from the whole relevant phase space. Using a number of real-world, complex mutualistic networks as a paradigm, we discover a scaling law between this probability and the rate of parameter change and provide a geometric theory to explain the law. The real-world implication is that even a slow parameter change can lead to a system collapse with catastrophic consequences. In fact, to mitigate the environmental changes by merely slowing down the parameter drift may not always be effective: only when the rate of parameter change is reduced to practically zero would the tipping be avoided. Our global dynamics approach offers a more complete and physically meaningful way to understand the important phenomenon of R-tipping.Comment: 8 pages, 5 figure

Machine-learning prediction of tipping and collapse of the Atlantic Meridional Overturning Circulation

Recent research on the Atlantic Meridional Overturning Circulation (AMOC) raised concern about its potential collapse through a tipping point due to the climate-change caused increase in the freshwater input into the North Atlantic. The predicted time window of collapse is centered about the middle of the century and the earliest possible start is approximately two years from now. More generally, anticipating a tipping point at which the system transitions from one stable steady state to another is relevant to a broad range of fields. We develop a machine-learning approach to predicting tipping in noisy dynamical systems with a time-varying parameter and test it on a number of systems including the AMOC, ecological networks, an electrical power system, and a climate model. For the AMOC, our prediction based on simulated fingerprint data and real data of the sea surface temperature places the time window of a potential collapse between the years 2040 and 2065.Comment: 6 pages, 3 figure

Usporedba djelovanja blokatora kalcijevih kanala, blokatora autonomnoga živčanog sustava te inhibitora slobodnih radikala na hiposekreciju inzulin iz izolirnih langerhansovih otočića štakora uzrokovanu diazinonom

Hyperglycaemia has been observed with exposure to organophosphate insecticides. This study was designed to compare the effects of calcium channel blockers, alpha-adrenergic, beta-adrenergic, and muscarinic receptor blockers, and of free radical scavengers on insulin secretion from diazinon-treated islets of Langerhans isolated from the pancreas of rats using standard collagenase digestion, separation by centrifugation, and hand-picking technique. The islets were then cultured in an incubator at 37 °C and 5 % CO2. In each experimental set 1 mL of 8 mmol L-1 glucose plus 125 µg mL-1 or 625 µg mL-1 of diazinon were added, except for the control group, which received 8 mmol L-1 glucose alone. The cultures were then treated with one of the following: 30 µmol L-1 atropine, 100 µmol L-1 ACh + 10 µmol L-1 neostigmine, 0.1 µmol L-1 propranolol, 2 µmol L-1 nifedipine, 50 µmol L-1 phenoxybenzamine, or 10 µmol L-1 alphatocopherol. In all experiments, diazinon significantly reduced glucose-stimulated insulin secretion at both doses, showing no dose dependency, as the average inhibition for the lower dose was 62.20 % and for the higher dose 64.38 %. Acetylcholine and alpha-tocopherol restored, whereas atropine potentiated diazinoninduced hyposecretion of insulin. Alpha-, beta- and calcium channel blockers did not change diazinoninduced effects. These findings suggest that diazinon affects insulin secretion mainly by disturbing the balance between free radicals and antioxidants in the islets of Langerhans and by inducing toxic stress.U osoba izloženih organofosfatnim insekticidima zamijećen je nastanak hiperglikemije. Svrha je ovo istraživanja bila usporediti djelovanje blokatora kalcijevih kanala, alfa i beta-adrenergičkih i muskarinskih receptora te inhibicije slobodnih radikala na lučenje inzulina iz Langerhansovih otočića izoliranih iz štakora tretiranih diazinonom. Otočići su izolirani iz gušterače štakora s pomoću standardnog postupka digestije kolagenazom, odvajanja centrifugiranjem i metodom ručnog probira (engl. hand-picking) te su kultivirani u inkubatoru pri 37 °C i 5 % CO2. Pokusne su kulture inkubirane s 1 mL glukoze u koncentraciji od 8 mmol L-1 te diazinonom u dozi od 125 μg mL-1, odnosno 625 μg mL-1. U kontrolu je dodana samo glukoza u koncentraciji od 8 mmol L-1. Nakon toga je u kulture dodan jedan od sljedećih agenasa: 30 µmol L-1 atropin, 100 µmol L-1 ACh + 10 µmol L-1 neostigmin, 0,1 µmol L-1 propranolol, 2 µmol L-1 nifedipin, 50 µmol L-1 fenoksibenzamin, odnosno 10 µmol L-1 alfa-tokoferol. U svim je pokusima diazinon značajno smanjio lučenje inzulina, s time da je doza od 125 μg mL-1 dovela do 62,2 %-tne inhibicije, a doza od 625 μg mL-1 do 64,38 %-tne inhibicije lučenja inzulina, što upućuje na djelovanje neovisno o dozi. Acetilkolin i alfa-tokoferol su ponovno potaknuli lučenje inzulina, za razliku od atropina koji ga je dodatno smanjio. Primjena blokatora alfa i beta-adrenergičkih receptora te blokatora kalcijevih kanala nije utjecala na djelovanje diazinona. Autori zaključuju da diazinon utječe na lučenje inzulina ponajviše narušavanjem ravnoteže između slobodnih radikala i antioksidansa u Langerhansovim otočićima te dovodi do toksičnoga stresa

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Milk and its Components in the Regulation of Short-term Appetite, Food Intake and Glycemia in Young Adults

The hypothesis that milk consumption decreases short-term appetite and food intake and improves glycemic control compared with other caloric beverages in healthy young adults was explored in four experiments. The first two experiments compared isovolumetric amounts (500 ml) of milk (2% M.F.), chocolate milk (1% M.F.), a soy beverage, infant formula, orange juice and water on satiety and food intake and blood glucose before and after a meal provided at 30 min (Experiment 1) and 120 min (Experiment 2). Pre-meal ingestion of chocolate milk and infant formula (highest in calories) reduced food intake at 30 min, but not 2 h. Only milk reduced post-meal blood glucose in both experiments suggesting that its macronutrient composition is a factor in blood glucose control. Experiment 3 compared the effects of ad libitum consumption of milk (1% M.F.), regular cola, diet cola, orange juice and water at a pizza meal on fluid and ad libitum food intake and post-meal appetite and glycemia. Fluid volume consumed was similar, but all caloric beverages added to total meal-time energy intake. However, milk lowered post-meal blood glucose and appetite score. In Experiment 4, the effect of isovolumetric (500 ml) beverages of whole milk (3.25% M.F.) and each of its macronutrient components, protein (16 g), lactose (24 g), and fat (16 g) on glycemic control and gastrointestinal hormonal responses were examined. The reduction in post-prandial glycemia was mediated by interactions between its macronutrient components and associated with hormonal responses that slow stomach emptying and increase glucose disposal. Thus, the results of this research do not support the hypothesis that milk consumption decreases short-term appetite and food intake compared with other beverages; however, milk improves glycemic control by insulin-dependent and independent mechanisms.Ph

Synchronization in a network of chaotic memristive jerk oscillators

There is a growing attraction to memristive chaotic systems since last decades. This paper provides a complete dynamical analysis of a chaotic memristive jerk system. Complex behavior of this system is studied with the help of equilibrium analysis, state space plots of trajectories, and bifurcation and Lyapunov exponents’ diagrams. The equilibrium analysis reveals that this system can have no equilibrium or two equilibria depending on the value of the parameters. When it has no equilibrium, it’s strange attractor is hidden. The collective behavior of this chaotic oscillator in dynamical networks is investigated by master stability function (MSF) which checks the stability of the synchronization manifold. According to the MSF analysis, the identical network of memristive oscillator belongs to the network type I