Ablation of peroxisome proliferator activated receptor (PPAR) ␣, a lipid-activated transcription factor that regulates expression of -oxidative genes, results in profound metabolic abnormalities in liver and heart. In the present study we used PPAR␣ knockout (KO) mice to determine whether this transcription factor is essential for regulating fuel metabolism in skeletal muscle. When animals were challenged with exhaustive exercise or starvation, KO mice exhibited lower serum levels of glucose, lactate, and ketones and higher nonesterified fatty acids than wild type (WT) littermates. During exercise, KO mice exhausted earlier than WT and exhibited greater rates of glycogen depletion in liver but not skeletal muscle. Fatty acid oxidative capacity was similar between muscles of WT and KO when animals were fed and only 28% lower in KO muscles when animals were starved. Exercise-induced regulation and starvation-induced regulation of pyruvate-dehydrogenase kinase 4 and uncoupling protein 3, two classical and robustly responsive PPAR␣ target genes, were similar between WT and KO in skeletal muscle but markedly different between genotypes in heart. Real time quantitative PCR analyses showed that unlike in liver and heart, in mouse skeletal muscle PPAR␦ is severalfold more abundant than either PPAR␣ or PPAR␥. In both human and rodent myocytes, the highly selective PPAR␦ agonist GW742 increased fatty acid oxidation about 2-fold and induced expression of several lipid regulatory genes, including pyruvate-dehydrogenase kinase 4 and uncoupling protein 3, responses that were similar to those elicited by the PPAR␣ agonist GW647. These results show redundancy in the functions of PPARs ␣ and ␦ as transcriptional regulators of fatty acid homeostasis and suggest that in skeletal muscle high levels of the ␦-subtype can compensate for deficiency of PPAR␣.Peroxisome proliferator activated receptors (PPARs) 1 ␣, ␦, and ␥ comprise a family of nuclear hormone receptors that regulate systemic fatty acid metabolism via ligand-dependent transcriptional activation of target genes (1). Strong evidence indicates that their endogenous ligands consist of fatty acids and/or lipid metabolites and that they function to mediate adaptive metabolic responses to changes in systemic fuel availability (1, 2). PPAR␣, which is expressed most abundantly in tissues that are characterized by high rates of fatty acid oxidation (FAO), is considered the primary subtype that mediates lipid-induced activation of FAO genes (3). This premise is based largely on studies of PPAR␣ knockout (KO) mice, which, compared with wild type (WT) littermates, exhibit low rates of -oxidation and abnormal accumulation of neutral lipids in both cardiac and hepatic tissues (4, 5). The metabolic phenotype of KO mice is associated with decreased expression of FAO genes and failure of liver and heart to induce -oxidative pathways in response to physiological or pharmacological perturbations in lipid metabolism (4 -6). Taken together, these studies indicate that, at least in rodents,...
The growth arrest and DNA damage-inducible protein, GADD34, was identified by its interaction with human inhibitor 1 (I-1), a protein kinase A (PKA)-activated inhibitor of type 1 protein serine/threonine phosphatase (PP1), in a yeast two-hybrid screen of a human brain cDNA library. Recombinant GADD34 (amino acids 233 to 674) bound both PKA-phosphorylated and unphosphorylated I-1(1-171). Serial truncations mapped the C terminus of I-1 (amino acids 142 to 171) as essential for GADD34 binding. In contrast, PKA phosphorylation was required for PP1 binding and inhibition by the N-terminal I-1(1-80) fragment. Pulldowns of GADD34 proteins expressed in HEK293T cells showed that I-1 bound the central domain of GADD34 (amino acids 180 to 483). By comparison, affinity isolation of cellular GADD34/PP1 complexes showed that PP1 bound near the C terminus of GADD34 (amino acids 483 to 619), a region that shows sequence homology with the virulence factors ICP34.5 of herpes simplex virus and NL-S of avian sarcoma virus. While GADD34 inhibited PP1-catalyzed dephosphorylation of phosphorylase a, the GADD34-bound PP1 was an active eIF-2␣ phosphatase. In brain extracts from active ground squirrels, GADD34 bound both I-1 and PP1 and eIF-2␣ was largely dephosphorylated. In contrast, the I-1/GADD34 and PP1/GADD34 interactions were disrupted in brain from hibernating animals, in which eIF-2␣ was highly phosphorylated at serine-51 and protein synthesis was inhibited. These studies suggested that modification of the I-1/GADD34/PP1 signaling complex regulates the initiation of protein translation in mammalian tissues.
Using new household survey data for 1995 and 2002, we investigate the size of China's urban-rural income gap, the gap's contribution to overall inequality in China, and the factors underlying the gap. Our analysis improves on past estimates by using a fuller measure of income, adjusting for spatial price differences and including migrants. Our methods include inequality decomposition by population subgroup and the Oaxaca-Blinder decomposition. Several key findings emerge. First, the adjustments substantially reduce China's urban-rural income gap and its contribution to inequality. Nevertheless, the gap remains large and has increased somewhat over time. Second, after controlling for household characteristics, location of residence remains the most important factor underlying the urban-rural income gap. The only household characteristic that contributes substantially to the gap is education. Differences in the endowments of, and returns to, other household characteristics such as family size and composition, landholdings, and Communist Party membership are relatively unimportant.
We present a novel approximation algorithm for k-median that achieves an approximation guarantee of 1 + √ 3 + ϵ, improving upon the decade-old ratio of 3 + ϵ. Our approach is based on two components, each of which, we believe, is of independent interest.First, we show that in order to give an α-approximation algorithm for k-median, it is sufficient to give a pseudoapproximation algorithm that finds an α-approximate solution by opening k+O(1) facilities. This is a rather surprising result as there exist instances for which opening k + 1 facilities may lead to a significant smaller cost than if only k facilities were opened.Second, we give such a pseudo-approximation algorithm with α = 1+ √ 3+ϵ. Prior to our work, it was not even known whether opening k + o(k) facilities would help improve the approximation ratio.
The paper examines the contentious issue of the extent of surplus labour that remains in China. China was an extreme example of a surplus labour economy, but the rapid economic growth during the period of economic reform requires a reassessment of whether the second stage of the Lewis model has been reached or is imminent. The literature is inconclusive. On the one hand, there are reports of migrant labour scarcity and rising migrant wages; on the other hand, estimates suggest that a considerable pool of relatively unskilled labour is still available in the rural sector. Yet the answer has far-reaching developmental and distributional implications. After reviewing the literature, the paper uses the 2002 and 2007 national household surveys of the Chinese Academy of Social Sciences to analyse and explain migrant wage behaviour, to predict the determinants of migration, and to examine the size and nature of the pool of potential rural-urban migrants. An attempt is also made to project the rural and urban labour force and migration forward to 2020, on the basis of the 2005 one per cent Population Survey. The paper concludes that for institutional reasons both phenomena are likely to coexist at present and for some time in the future.
578 Background: Atezolizumab (atezo; anti–PD-L1) + bevacizumab (bev; anti-VEGF) showed first-line (1L) anti-tumor activity with a manageable safety profile in PD-L1+ mRCC pts in a Phase II study (McDermott ASCO-GU 2017). Here we describe the first randomized Phase III trial of a PD-L1/PD-1 pathway inhibitor combined with an anti-VEGF agent in 1L mRCC. Methods: IMmotion151 (NCT02420821) enrolled treatment-naïve pts regardless of prognostic risk group randomized 1:1 to receive atezo 1200 mg IV q3w + bev 15 mg/kg IV q3w or sunitinib (sun) 50 mg PO QD 4 wk on/2 wk off. Pts were stratified by PD-L1 status (< 1% vs ≥ 1% PD-L1 expression on tumor-infiltrating immune cells [IC]; SP142 IHC assay). Coprimary endpoints: progression-free survival (PFS; by investigator per RECIST v1.1) in PD-L1+ pts (≥ 1% IC) and overall survival (OS) in intent-to-treat (ITT) pts. Secondary endpoints included PFS in ITT pts, ORR and DOR. Results: Baseline characteristics were comparable between arms within PD-L1+ (40% of ITT) and ITT pts. Median survival follow-up was 15 mo. PFS HR for atezo + bev vs sun was 0.74 (95% CI 0.57, 0.96) in PD-L1+ pts and 0.83 (95% CI 0.70, 0.97) in ITT pts. OS was immature at first interim analysis. PFS benefit was consistent across analyzed subgroups, including MSKCC risk, liver metastases and sarcomatoid histology. In PD-L1+ pts, ORR was 43% and DOR was not reached for atezo + bev vs 35% and 12.9 mo for sun. 40% of atezo + bev–treated pts and 54% of sun-treated pts had treatment-related Gr 3-4 AEs; 12% and 8% of treatment-related all-Gr AEs led to discontinuation, respectively. Conclusions: The study showed longer PFS for atezo + bev vs sun in PD-L1+ pts. Improved PFS was also observed in ITT pts. Safety was consistent with that of the individual agents. These results support the use of atezo + bev as a 1L treatment option in mRCC. Clinical trial information: NCT02420821. [Table: see text]
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.