Citations

Abstract Renal fibrosis is the common pathological hallmark of progressive chronic kidney disease ( CKD ) with diverse aetiologies. Recent researches have highlighted the critical role of hypoxia during the development of renal fibrosis as a final common pathway in end‐stage kidney disease ( ESKD ), which joints the scientist's attention recently to exploit the molecular mechanism underlying hypoxia‐induced renal fibrogenesis. The scaring formation is a multilayered cellular response and involves the regulation of multiple hypoxia‐inducible signalling pathways and complex interactive networks. Therefore, this review will focus on the signalling pathways involved in hypoxia‐induced pathogenesis of interstitial fibrosis, including pathways mediated by HIF , TGF ‐β, Notch, PKC / ERK , PI 3K/Akt, NF ‐κB, Ang II / ROS and micro RNA s. Roles of molecules such as IL ‐6, IL ‐18, KIM ‐1 and ADO are also reviewed. A comprehensive understanding of the roles that these hypoxia‐responsive signalling pathways and molecules play in the context of renal fibrosis will provide a foundation towards revealing the underlying mechanisms of progression of CKD and identifying novel therapeutic targets. In the future, promising new effective therapy against hypoxic effects may be successfully translated into the clinic to alleviate renal fibrosis and inhibit the progression of CKD .

Key Points An international panel established the first ever diagnostic criteria for iMCD based on review of 244 clinical cases and 88 tissue samples. The criteria require multicentric lymphadenopathy with defined histopathology, ≥2 clinical/laboratory changes, and exclusion of iMCD mimics.

Abstract Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignancies lacking effective therapeutic strategies. Here, we show that the noncanonical IκB-related kinase, IKBKE, is a critical oncogenic effector during KRAS-induced pancreatic transformation. Loss of IKBKE inhibits the initiation and progression of pancreatic tumors in mice carrying pancreatic-specific KRAS activation. Mechanistically, we demonstrate that this protumoral effect of IKBKE involves the activation of GLI1 and AKT signaling and is independent of the levels of activity of the NF-κB pathway. Further analysis reveals that IKBKE regulates GLI1 nuclear translocation and promotes the reactivation of AKT post-inhibition of mTOR in PDAC cells. Interestingly, combined inhibition of IKBKE and mTOR synergistically blocks pancreatic tumor growth. Together, our findings highlight the functional importance of IKBKE in pancreatic cancer, support the evaluation of IKBKE as a therapeutic target in PDAC, and suggest IKBKE inhibition as a strategy to improve efficacy of mTOR inhibitors in the clinic. Cancer Res; 77(2); 320–9. ©2017 AACR.

Background and purposeIntensity‐modulated proton therapy (IMPT) is highly sensitive to range uncertainties and uncertainties caused by setup variation. The conventional inverse treatment planning of IMPT based on the planning target volume (PTV) is not often sufficient to ensure robustness of treatment plans. We applied a probabilistic framework (chance‐constrained optimization) in IMPT planning to hedge against the influence of uncertainties.Material and methodsWe retrospectively selected one patient with lung cancer, one patient with head and neck (H&N) cancer, and one with prostate cancer for this analysis. Using their original images and prescriptions, we created new IMPT plans using two methods: (1) a robust chance‐constrained treatment planning method with the clinical target volume (CTV) as the target; (2) the margin‐based method with PTV as the target, which was solved by commercial software, CPLEX, using linear programming. For the first method, we reformulated the model into a tractable mixed‐integer programming problem and sped up the calculation using Benders decomposition. The dose‐volume histograms (DVHs) from the nominal and perturbed dose distributions were used to assess and compare plan quality. DVHs for all uncertain scenarios along with the nominal DVH were plotted. The width of the “bands” of DVHs was used to quantify the plan sensitivity to uncertainty. The newly developed Benders decomposition method was compared with a commercial solution to demonstrate its computational efficiency. The trade‐off between nominal plan quality and plan robustness was investigated.ResultsOur chance‐constrained model outperformed the PTV method in terms of tumor coverage, tumor dose homogeneity, and plan robustness. Our model was shown to produce IMPT plans to meet the dose‐volume constraints of organs at risk (OARs) and had better sparing of OARs than the PTV method in the three clinical cases included in this study. The chance‐constrained model provided a flexible tool for users to balance between plan robustness and plan quality. In addition, our in‐house developed method was found to be much faster than the commercial solution.ConclusionWith explicit control of plan robustness, the chance‐constrained robust optimization model generated superior IMPT plans compared to the PTV‐based method.

A generalized ensemble model (gEnM) for document ranking is proposed in this paper. The gEnM linearly combines the document retrieval models and tries to retrieve relevant documents at high positions. In order to obtain the optimal linear combination of multiple document retrieval models or rankers, an optimization program is formulated by directly maximizing the mean average precision. Both supervised and unsupervised learning algorithms are presented to solve this program. For the supervised scheme, two approaches are considered based on the data setting, namely batch and online setting. In the batch setting, we propose a revised Newton?s algorithm, gEnM.BAT, by approximating the derivative and Hessian matrix. In the online setting, we advocate a stochastic gradient descent (SGD) based algorithm-gEnM.ON. As for the unsupervised scheme, an unsupervised ensemble model (UnsEnM) by iteratively co-learning from each constituent ranker is presented. Experimental study on benchmark data sets verifies the effectiveness of the proposed algorithms. Therefore, with appropriate algorithms, the gEnM is a viable option in diverse practical information retrieval applications.

Prohibitin 1 (PHB1) is best known as a mitochondrial chaperone, and its role in cancer is conflicting. Mice lacking methionine adenosyltransferase α1 (MATα1) have lower PHB1 expression, and we reported that c‐MYC interacts directly with both proteins. Furthermore, c‐MYC and MATα1 exert opposing effects on liver cancer growth, prompting us to examine the interplay between PHB1, MATα1, and c‐MYC and PHB1's role in liver tumorigenesis. We found that PHB1 is highly expressed in normal hepatocytes and bile duct epithelial cells and down‐regulated in most human hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA). In HCC and CCA cells, PHB1 expression correlates inversely with growth. PHB1 and MAT1A positively regulate each other's expression, whereas PHB1 negatively regulates the expression of c‐MYC, MAFG, and c‐MAF. Both PHB1 and MATα1 heterodimerize with MAX, bind to the E‐box element, and repress E‐box promoter activity. PHB1 promoter contains a repressive E‐box element and is occupied mainly by MAX, MNT, and MATα1 in nonmalignant cholangiocytes and noncancerous tissues that switched to c‐MYC, c‐MAF, and MAFG in cancer cells and human HCC/CCA. All 8‐month‐old liver‐specific Phb1 knockout mice developed HCC, and one developed CCA. Five‐month‐old Phb1 heterozygotes, but not Phb1 flox mice, developed aberrant bile duct proliferation; and one developed CCA 3.5 months after left and median bile duct ligation. Phb1 heterozygotes had a more profound fall in the expression of glutathione synthetic enzymes and higher hepatic oxidative stress following left and median bile duct ligation. Conclusion: We have identified that PHB1, down‐regulated in most human HCC and CCA, heterodimerizes with MAX to repress the E‐box and positively regulates MAT1A while suppressing c‐MYC, MAFG, and c‐MAF expression; in mice, reduced PHB1 expression predisposes to the development of cholestasis‐induced CCA. (Hepatology 2017;65:1249‐1266).

A novel protein complex facilitates lipid droplet autophagy.