PGC-1α is an inducible transcriptional coactivator that regulates mitochondrial biogenesis and cellular energy metabolism in skeletal muscle. Recent studies have identified two additional PGC-1α transcripts that are derived from an alternative exon 1 (exon 1b) and induced by exercise. Given that the PGC-1α gene also produces NT-PGC-1α transcript by alternative 3′ splicing between exon 6 and exon 7, we have investigated isoform-specific expression of NT-PGC-1α mRNA in mouse skeletal muscle during physical exercise with different intensities. We report here that NT-PGC-1α-a mRNA expression derived from a canonical exon 1 (exon 1a) is increased by high-intensity exercise and AMPK activator AICAR in mouse skeletal muscle but not altered by low- and medium-intensity exercise and β 2-adrenergic receptor agonist clenbuterol. In contrast, the alternative exon 1b-driven NT-PGC-1α-b (PGC-1α4) and NT-PGC-1α-c are highly induced by low-, medium-, and high-intensity exercise, AICAR, and clenbuterol. Ectopic expression of NT-PGC-1α-a in C2C12 myotube cells upregulates myosin heavy chain (MHC I, MHC II a) and Glut4, which represent oxidative fibers, and promotes the expression of mitochondrial genes (Cyc1, COX5B, and ATP5B). In line with gene expression data, citrate synthase activity was significantly increased by NT-PGC-1α-a in C2C12 myotube cells. Our results indicate the regulatory role for NT-PGC-1α-a in mitochondrial biogenesis and adaptation of skeletal muscle to endurance exercise.

Self-assembled cages have emerged as novel platforms to explore bio-inspired catalysis. While many different size and shape supramolecular structures are now readily accessible, only a few are known to accelerate chemical reactions under substoichiometric conditions. These limited examples point to a poor understanding of cage catalysis in general, limiting the ability to design new systems. Here we show that a simple and efficient density functional theory-based methodology, informed by explicitly solvated molecular dynamics and coupled cluster calculations is sufficient to accurately reproduce experimental guest binding affinities (MAD = 1.9 kcal mol -1 ) and identify the catalytic Diels-Alder proficiencies (>80 % accuracy) of two homologous Pd2L4 metallocages with a variety of substrates. This analysis reveals how subtle structural differences in the cage framework affect binding and catalysis. These effects manifest in a smaller distortion and more favorable interaction energy for the catalytic cage compared to the inactive structure. This study gives a detailed insight that would otherwise be difficult to obtain from experiments, providing new opportunities in the design catalytically active supramolecular cages.

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Carbon-Carbon bond forming processes that involve the deprotonation of a weakly acidic C-H pro-nucleophile using a strong Brønsted base are central to synthetic methodology. Enzymes also catalyze C-C bond formation from weakly C-H acidic substrates, however, they accomplish this at pH 7 using only collections of non-covalent interactions. Here we show that a simple, bio-inspired synthetic cage catalyzes Michael addition reactions using only coulombic and other weak interactions to activate various pro-nucleophiles and electrophiles. The anion-stabilizing property of the cage promotes spontaneous pro-nucleophile deprotonation, suggesting acidity-enhancement equivalent to several pKa units. Using a second non-covalent reagentcommercially available 18-crown-6facilitates catalytic base-free addition of several challenging Michael partners. The cage's microenvironment also promotes high diastereoselectivity compared to a conventional base-catalyzed reaction.

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An accurate information on the amount and location of Land use and land cover (LULC) changes is necessary to develop and implement a sustainable-urban planning.This research investigates the potential of an integrated Multi-Layer Perceptron and Markov Chain Analysis (MLP-MCA) to map and accurately predict the future LULC change scenarios in Lagos Metropolitan Region of Nigeria. Multi-temporal LULC datasets derived from remotely sensed Landsat images from 1984, 2000 and 2015 were used for modeling, validation and prediction. Predicted LULC changes for 2030 and 2050 were performed based on the LULC map of 2015 using MLP-MCA method. The result reveals a significant expansion of built-up areas during the whole study period. Analysis of LULC distribution in Lagos metropolitan region shows that about 50% of urban land expansion happened beyond the administrative boundary of Lagos State during the period of 2000-2015. It is predicted that more than 75% of future urban growth will occur across the border of Lagos State, in the neighbouring Ogun State by 2050. These results imply that a strong and consistent collaboration between different states is crucial to establish an effective regional planning framework and ensure a proper planned growth of the metropolitan region.ARTICLE HISTORY