Branched-Chain Amino Acid Negatively Regulates KLF15 Expression via PI3K-AKT Pathway.

Recent studies have linked branched-chain amino acid (BCAA) with numerous metabolic diseases. However, the molecular basis of BCAA's roles in metabolic regulation remains to be established. KLF15 (Krüppel-like factor 15) is a transcription factor and master regulator of glycemic, lipid, and amino acids metabolism. In the present study, we found high concentrations of BCAA suppressed KLF15 expression while BCAA starvation induced KLF15 expression, suggesting KLF15 expression is negatively controlled by BCAA.Interestingly, BCAA starvation induced PI3K-AKT signaling. KLF15 induction by BCAA starvation was blocked by PI3K and AKT inhibitors, indicating the activation of PI3K-AKT signaling pathway mediated the KLF15 induction. BCAA regulated KLF15 expression at transcriptional level but not post-transcriptional level. However, BCAA starvation failed to increase the KLF15-promoter-driven luciferase expression, suggesting KLF15 promoter activity was not directly controlled by BCAA. Finally, fasting reduced BCAA abundance in mice and KLF15 expression was dramatically induced in muscle and white adipose tissue, but not in liver. Together, these data demonstrated BCAA negatively regulated KLF15 expression, suggesting a novel molecular mechanism underlying BCAA's multiple functions in metabolic regulation

Primary Forest Degradation and Secondary Re-growth Dynamics in the Brazilian Amazon

The Amazon rainforest is a vital biome that is of central importance for the provision of significant ecosystem services locally, regionally and globally. Brazil contains two-thirds of remaining Amazonian rainforests and is responsible for the majority of Amazonian forest loss. Over 0.7 million km^2 of primary forest area in the Brazilian Amazon has been deforested, of which ~20% are under secondary forest regeneration. However, the fate of secondary forests and the extent of degradation of the remaining primary forests (referred to as old growth forests in this thesis) are still unclear. In this thesis, I present: (1) the first large-scale analysis of secondary forest loss over 14 years (2000-2014) using recently released high resolution (30 m) post-deforestation land use datasets (TERRACLASS); (2) a novel machine learning classification method to map tropical forest disturbances using multi-decadal Landsat time-series imagery; and (3) first estimates of the historical degradation of remaining old growth forests using this newly-developed classification method. Our results show an accelerated loss of secondary forests across the entire Brazilian Amazon over our study period, in contrast to primary forest loss. Over 2000-2014, the proportion of total forest loss accounted for by secondary forests rose from (37 ± 3) % in 2000 to (72 ± 5) % in 2014. We developed a multi-decadal Landsat time-series imagery and machine learning random forest classification algorithm, which we found to be an efficient and accurate approach to map tropical disturbed forests. This approach allows me to map the historical degradation of old growth forests from 1984 to 2014. Until 2014, over 246,845 km^2 area of old-growth forests in the Brazilian Amazon (moist forest ecoregion) were degraded, accounted for approximately 10% of total area of old growth forests in the region. However, this approach may have underestimated the actual degradation of old growth forests as it did not detect the low intensity selective logging. In conclusion, the accelerated loss of secondary forests and extensive degradation of old growth forests in the Brazilian Amazon which we report have provided new insights into land use change dynamics in Amazonia. Both of these processes have important implications for carbon storage and biodiversity and sustainable management of forest resources in the Brazilian Amazon

The role of silicon, boron and pH-dependent aluminium speciation in solution on aluminium toxicity in maize (Zea mays L.)

[no abstract

Methadone-Induced Delayed Posthypoxic Encephalopathy: Clinical, Radiological, and Pathological Findings

Objective. To describe the clinical, radiological and pathological findings in a patient with methadone-induced delayed posthypoxic encephalopathy (DPHE). Case Report. A Thirty-eight-year-old man was found unconscious for an unknown duration after methadone and diazepam ingestion. His initial vitals were temperature 104 degree Fahrenheit, heart rate 148/minute, respiratory rate 50/minute, and blood pressure 107/72 mmhg. He developed renal failure, rhabdomyolysis, and elevated liver enzymes which resolved completely in 6 days. After 2 weeks from discharge he had progressive deterioration of his cognitive, behavioral and neurological function. Brain MRI showed diffuse abnormal T2 signal in the corona radiata, centrum semiovale, and subcortical white matter throughout all lobes. Extensive work up was negative for any metabolic, infectious or autoimmune disorder. Brain biopsy showed significant axonal injury in the white matter. He was treated successfully with combination of steroids and antioxidants. Follow up at 2 year showed no residual deficits. Conclusion. Our observation suggests that patients on methadone therapy should be monitored for any neurological or psychiatric symptoms, and in suspected cases MRI brain may help to make the diagnosis of DPHE. A trial of steroids and antioxidants may be considered in these patients