Supramolecular coordination chemistry of aromatic polyoxalamide ligands: A metallosupramolecular approach toward functional magnetic materials

The impressive potential of the metallosupramolecular approach in designing new functional magnetic materials constitutes a great scientific challenge for the chemical research community that requires an interdisciplinary collaboration. New fundamental concepts and future applications in nanoscience and nanotechnology will emerge from the study of magnetism as a supramolecular function in metallosupramolecular chemistry. Our recent work on the rich supramolecular coordination chemistry of a novel family of aromatic polyoxalamide (APOXA) ligands with first-row transition metal ions has allowed us to move one step further in the rational design of metallosupramolecular assemblies of increasing structural and magnetic complexity. Thus, we have taken advantage of the new developments of metallosupramolecular chemistry and, in particular, the molecular-programmed self-assembly methods that exploit the coordination preferences of paramagnetic metal ions and suitable designed polytopic ligands. The resulting self-assembled di- and trinuclear metallacyclic complexes with APOXA ligands, either metallacyclophanes or metallacryptands, are indeed ideal model systems for the study of the electron exchange mechanism between paramagnetic metal centers through extended π-conjugated aromatic bridges. So, the influence of different factors such as the topology and conformation of the bridging ligand or the electronic configuration and magnetic anisotropy of the metal ion have been investigated in a systematic way. These oligonuclear metallacyclic complexes can be important in the development of a new class of molecular magnetic devices, such as molecular magnetic wires (MMWs) and switches (MMSs), which are major goals in the field of molecular electronics and spintronics. On the other hand, because of their metal binding capacity through the outer carbonyl-oxygen atoms of the oxamato groups, they can further be used as ligands, referred to as metal–organic ligands (MOLs), toward either coordinatively unsaturated metal complexes or fully solvated metal ions. This well-known “complex-as-ligand” approach affords a wide variety of high-nuclearity metal–organic clusters (MOCs) and high-dimensionality metal–organic polymers (MOPs). The judicious choice of the oligonuclear MOL, ranging from mono- to di- and trinuclear species, has allowed us to control the overall structure and magnetic properties of the final oxamato-bridged multidimensional (nD, n = 0–3) MOCs and MOPs. The intercrossing between short- (nanoscopic) and long-range (macroscopic) magnetic behavior has been investigated in this unique family of oxamato-bridged metallosupramolecular magnetic materials expanding the examples of low-dimensional, single-molecule (SMMs) and single-chain (SCMs) magnets and high-dimensional, open-framework magnets (OFMs), which are brand-new targets in the field of molecular magnetism and materials science

Device-measured physical activity and cardiometabolic health: the Prospective Physical Activity, Sitting, and Sleep (ProPASS) consortium

Background and Aims: Physical inactivity, sedentary behaviour (SB), and inadequate sleep are key behavioural risk factors of cardiometabolic diseases. Each behaviour is mainly considered in isolation, despite clear behavioural and biological interdependencies. The aim of this study was to investigate associations of five-part movement compositions with adiposity and cardiometabolic biomarkers.Methods: Cross-sectional data from six studies (n = 15 253 participants; five countries) from the Prospective Physical Activity, Sitting and Sleep consortium were analysed. Device-measured time spent in sleep, SB, standing, light-intensity physical activity (LIPA), and moderate-vigorous physical activity (MVPA) made up the composition. Outcomes included body mass index (BMI), waist circumference, HDL cholesterol, total:HDL cholesterol ratio, triglycerides, and glycated haemoglobin (HbA1c). Compositional linear regression examined associations between compositions and outcomes, including modelling time reallocation between behaviours.Results: The average daily composition of the sample (age: 53.7 ± 9.7 years; 54.7% female) was 7.7h sleeping, 10.4h sedentary, 3.1h standing, 1.5h LIPA, and 1.3h MVPA. A greater MVPA proportion and smaller SB proportion were associated with better outcomes. Reallocating time from SB, standing, LIPA, or sleep into MVPA resulted in better scores across all outcomes. For example, replacing 30min of SB, sleep, standing, or LIPA with MVPA was associated with-0.63 (95% confidence interval-0.48,-0.79),-0.43 (-0.25,-0.59),-0.40 (-0.25,-0.56), and-0.15 (0.05,-0.34) kg/m2 lower BMI, respectively. Greater relative standing time was beneficial, whereas sleep had a detrimental association when replacing LIPA/MVPA and positive association when replacing SB. The minimal displacement of any behaviour into MVPA for improved cardiometabolic health ranged from 3.8 (HbA1c) to 12.7 (triglycerides) min/day. Conclusions: Compositional data analyses revealed a distinct hierarchy of behaviours. Moderate-vigorous physical activity demonstrated the strongest, most time-efficient protective associations with cardiometabolic outcomes. Theoretical benefits from reallocating SB into sleep, standing, or LIPA required substantial changes in daily activity.</p

Device-measured physical activity and cardiometabolic health: the Prospective Physical Activity, Sitting, and Sleep (ProPASS) consortium

BACKGROUND AND AIMS: Physical inactivity, sedentary behaviour (SB), and inadequate sleep are key behavioural risk factors of cardiometabolic diseases. Each behaviour is mainly considered in isolation, despite clear behavioural and biological interdependencies. The aim of this study was to investigate associations of five-part movement compositions with adiposity and cardiometabolic biomarkers. METHODS: Cross-sectional data from six studies (n = 15 253 participants; five countries) from the Prospective Physical Activity, Sitting and Sleep consortium were analysed. Device-measured time spent in sleep, SB, standing, light-intensity physical activity (LIPA), and moderate-vigorous physical activity (MVPA) made up the composition. Outcomes included body mass index (BMI), waist circumference, HDL cholesterol, total:HDL cholesterol ratio, triglycerides, and glycated haemoglobin (HbA1c). Compositional linear regression examined associations between compositions and outcomes, including modelling time reallocation between behaviours. RESULTS: The average daily composition of the sample (age: 53.7 ± 9.7 years; 54.7% female) was 7.7 h sleeping, 10.4 h sedentary, 3.1 h standing, 1.5 h LIPA, and 1.3 h MVPA. A greater MVPA proportion and smaller SB proportion were associated with better outcomes. Reallocating time from SB, standing, LIPA, or sleep into MVPA resulted in better scores across all outcomes. For example, replacing 30 min of SB, sleep, standing, or LIPA with MVPA was associated with -0.63 (95% confidence interval -0.48, -0.79), -0.43 (-0.25, -0.59), -0.40 (-0.25, -0.56), and -0.15 (0.05, -0.34) kg/m2 lower BMI, respectively. Greater relative standing time was beneficial, whereas sleep had a detrimental association when replacing LIPA/MVPA and positive association when replacing SB. The minimal displacement of any behaviour into MVPA for improved cardiometabolic health ranged from 3.8 (HbA1c) to 12.7 (triglycerides) min/day. CONCLUSIONS: Compositional data analyses revealed a distinct hierarchy of behaviours. Moderate-vigorous physical activity demonstrated the strongest, most time-efficient protective associations with cardiometabolic outcomes. Theoretical benefits from reallocating SB into sleep, standing, or LIPA required substantial changes in daily activity

Protein-protein interaction (PPI) network analysis reveals important hub proteins and sub-network modules for root development in rice (Oryza sativa)

Abstract Background The root system is vital to plant growth and survival. Therefore, genetic improvement of the root system is beneficial for developing stress-tolerant and improved plant varieties. This requires the identification of proteins that significantly contribute to root development. Analyzing protein-protein interaction (PPI) networks is vastly beneficial in studying developmental phenotypes, such as root development, because a phenotype is an outcome of several interacting proteins. PPI networks can be analyzed to identify modules and get a global understanding of important proteins governing the phenotypes. PPI network analysis for root development in rice has not been performed before and has the potential to yield new findings to improve stress tolerance. Results Here, the network module for root development was extracted from the global Oryza sativa PPI network retrieved from the STRING database. Novel protein candidates were predicted, and hub proteins and sub-modules were identified from the extracted module. The validation of the predictions yielded 75 novel candidate proteins, 6 sub-modules, 20 intramodular hubs, and 2 intermodular hubs. Conclusions These results show how the PPI network module is organized for root development and can be used for future wet-lab studies for producing improved rice varieties