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91.
The transcription factor Cabut coordinates energy metabolism and the circadian clock in response to sugar sensing
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Litman P Ohne O Ben-Yaakov S Shemesh-Darvish L Yechezkel T Salitra Y Rubnov S Cohen I Senderowitz H Kidron D Livnah O Levitzki A Livnah N 《Biochemistry》2007,46(16):4716-4724
We describe a novel, potent peptide substrate mimetic inhibitor of protein kinase B (PKB/Akt). The compound selectively kills prostate cancer cells, in which PKB is highly activated, but not normal cells, or cancer cells in which PKB is not activated. The inhibitor induces apoptosis and inhibits the phosphorylation of PKB substrates in prostate cancer cell lines and significantly increases the efficacy of chemotherapy agents to induce prostate cancer cell death, when given in combination. In vivo, the inhibitor exhibits a strong antitumor effect in two prostate cancer mouse models. Moreover, treated animals develop significantly less lung metastases compared to untreated ones, and the effect is accompanied by a significant decrease in blood PSA [prostate-specific antigen] levels in treated animals. This compound and its potential analogues may be developed into novel, potent, and safe anticancer agents, both as stand-alone treatment and in combination with other chemotherapy agents. 相似文献
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Esther Levy Ran Kornowski Reut Gavrieli Ilana Fratty Gabriel Greenberg Maayan Waldman Einat Birk Asher Shainberg Amit Akirov Ruth Miskin Edith Hochhauser 《PloS one》2015,10(12)
αMUPA transgenic mice spontaneously consume less food compared with their wild type (WT) ancestors due to endogenously increased levels of the satiety hormone leptin. αMUPA mice share many benefits with mice under caloric restriction (CR) including an extended life span. To understand mechanisms linked to cardiac aging, we explored the response of αMUPA hearts to ischemic conditions at the age of 6, 18, or 24 months. Mice were subjected to myocardial infarction (MI) in vivo and to ischemia/reperfusion ex vivo. Compared to WT mice, αMUPA showed functional and histological advantages under all experimental conditions. At 24 months, none of the WT mice survived the first ischemic day while αMUPA mice demonstrated 50% survival after 7 ischemic days. Leptin, an adipokine decreasing under CR, was consistently ~60% higher in αMUPA sera at baseline. Leptin levels gradually increased in both genotypes 24h post MI but were doubled in αMUPA. Pretreatment with leptin neutralizing antibodies or with inhibitors of leptin signaling (AG-490 and Wortmannin) abrogated the αMUPA benefits. The antibodies also reduced phosphorylation of the leptin signaling components STAT3 and AKT specifically in the αMUPA myocardium. αMUPA mice did not show elevation in adiponectin, an adipokine previously implicated in CR-induced cardioprotection. WT mice treated for short-term CR exhibited cardioprotection similar to that of αMUPA, however, along with increased adiponectin at baseline. Collectively, the results demonstrate a life-long increased ischemic tolerance in αMUPA mice, indicating the attenuation of cardiac aging. αMUPA cardioprotection is mediated through endogenous leptin, suggesting a protective pathway distinct from that elicited under CR. 相似文献
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Recent advances in T cell repertoire (TCR) sequencing allow for the characterization of repertoire properties, as well as the frequency and sharing of specific TCR. However, there is no efficient measure for the local density of a given TCR. TCRs are often described either through their Complementary Determining region 3 (CDR3) sequences, or theirV/J usage, or their clone size. We here show that the local repertoire density can be estimated using a combined representation of these components through distance conserving autoencoders and Kernel Density Estimates (KDE). We present ELATE–an Encoder-based LocAl Tcr dEnsity and show that the resulting density of a sample can be used as a novel measure to study repertoire properties. The cross-density between two samples can be used as a similarity matrix to fully characterize samples from the same host. Finally, the same projection in combination with machine learning algorithms can be used to predict TCR-peptide binding through the local density of known TCRs binding a specific target. 相似文献
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