Search

Posiphen tartrate (Posiphen) is an orally available small molecule that targets a conserved regulatory element in the mRNAs of amyloid precursor protein (APP) and α-synuclein (αSYN) and inhibits their translation. APP and αSYN can cause neurodegeneration when their aggregates induce neurotoxicity. Therefore, Posiphen is a promising drug candidate for neurodegenerative diseases, including Alzheimer's disease and Parkinson's disease. Posiphen's safety has been demonstrated in three independent phase I clinical trials. Moreover, in a proof of concept study, Posiphen lowered neurotoxic proteins and inflammatory markers in cerebrospinal fluid of mild cognitive impaired patients. Herein we investigated whether Posiphen reduced the expression of other proteins, as assessed by stable isotope labeling with amino acids in cell culture (SILAC) followed by mass spectrometry (MS)-based proteomics. Neuroblastoma SH-SY5Y cells, an in vitro model of neuronal function, were used for the SILAC protein profiling response. Proteins whose expression was altered by Posiphen treatment were characterized for biological functions, pathways and networks analysis. The most significantly affected pathway was the Huntington's disease signaling pathway, which, along with huntingtin (HTT) protein, was down-regulated by Posiphen in the SH-SY5Y cells. The downregulation of HTT protein by Posiphen was confirmed by quantitative Western blotting and immunofluorescence. Unchanged mRNA levels of HTT and a comparable decay rate of HTT proteins after Posiphen treatment supported the coclusion that Posiphen reduced HTT via downregulation of the translation of HTT mRNA. Meanwhile, the downregulation of APP and αSYN proteins by Posiphen was also confirmed. The mRNAs encoding HTT, APP and αSYN contain an atypical iron response element (IRE) in their 5'-untranslated regions (5'-UTRs) that bind iron regulatory protein 1 (IRP1), and Posiphen specifically bound this complex. Conversely, Posiphen did not bind the IRP1/IRE complex of mRNAs with canonical IREs, and the translation of these mRNAs was not affected by Posiphen. Taken together, Posiphen shows high affinity binding to the IRE/IRP1 complex of mRNAs with an atypical IRE stem loop, inducing their translation suppression, including the mRNAs of neurotoxic proteins APP, αSYN and HTT.

The term 'undruggable' was coined to describe proteins that could not be targeted pharmacologically. However, progress is being made to 'drug' many of these targets, and therefore more appropriate terms might be 'difficult to drug' or 'yet to be drugged'. Many desirable targets in cancer fall into this category, including the RAS and MYC oncogenes, and pharmacologically targeting these intractable proteins is now a key challenge in cancer research that requires innovation and the development of new technologies. In this Viewpoint article, we asked four scientists working in this field for their opinions on the most crucial advances, as well as the challenges and what the future holds for this important area of research.

Multiple myeloma is a fatal plasma cell neoplasm accounting for over 10,000 deaths in the United States each year. Despite new therapies, multiple myeloma remains incurable, and patients ultimately develop drug resistance and succumb to the disease. The response to selective CDK4/6 inhibitors has been modest in multiple myeloma, potentially because of incomplete targeting of other critical myeloma oncogenic kinases. As a substantial number of multiple myeloma cell lines and primary samples were found to express AMPK-related protein kinase 5(ARK5), a member of the AMPK family associated with tumor growth and invasion, we examined whether dual inhibition of CDK4 and ARK5 kinases using ON123300 results in a better therapeutic outcome. Treatment of multiple myeloma cell lines and primary samples with ON123300 in vitro resulted in rapid induction of cell-cycle arrest followed by apoptosis. ON123300-mediated ARK5 inhibition or ARK5-specific siRNAs resulted in the inhibition of the mTOR/S6K pathway and upregulation of the AMPK kinase cascade. AMPK upregulation resulted in increased SIRT1 levels and destabilization of steady-state MYC protein. Furthermore, ON123300 was very effective in inhibiting tumor growth in mouse xenograft assays. In addition, multiple myeloma cells sensitive to ON123300 were found to have a unique genomic signature that can guide the clinical development of ON123300. Our study provides preclinical evidence that ON123300 is unique in simultaneously inhibiting key oncogenic pathways in multiple myeloma and supports further development of ARK5 inhibition as a therapeutic approach in multiple myeloma.

In the data collection phase, the digital images are captured using sensors that often contaminated by noise (undesired random signal). In digital image processing task, enhancing the image quality and reducing the noise is a central process. Image denoising effectively preserves the image edges to a higher extend in the flat regions. Several adaptive filters (median filter, Gaussian filter, fuzzy filter, etc.) have been utilized to improve the smoothness of digital image, but these filters failed to preserve the image edges while removing noise. In this paper, a modified fuzzy set filter has been proposed to eliminate noise for restoring the digital image. Usually in fuzzy set filter, sixteen fuzzy rules are generated to find the noisy pixels in the digital image. In modified fuzzy set filter, a set of twenty-four fuzzy rules are generated with additional four pixel locations for determining the noisy pixels in the digital image. The additional eight fuzzy rules ease the process of finding the image pixels,whether it required averaging or not. In this scenario, the input digital images were collected from the underwater photography fish dataset. The efficiency of the modified fuzzy set filter was evaluated by varying degrees of Gaussian noise (0.01, 0.03, and 0.1 levels of Gaussian noise). For performance evaluation, Structural Similarity (SSIM), Mean Structural Similarity (MSSIM), Mean Square Error (MSE), Normalized Mean Square Error (NMSE), Universal Image Quality Index (UIQI), Peak Signal to Noise Ratio (PSNR), and Visual Information Fidelity (VIF) were used. The experimental results showed that the modified fuzzy set filter improved PSNR value up to 2-3 dB, MSSIM up to 0.12-0.03, and NMSE value up to 0.38-0.1 compared to the traditional filtering techniques.

In this study an attempt was made to assess the mining associated urbanization impact on rural agricultural lands due to expansion of mining dump yards, pulverizing mills and beneficiation plants in and around Govindampalle village, YSR District, A.P by using Geospatial technologies. Various land use and land cover (LULC) classes, mainly, cropland, plantation, fallow land, mining/industrial, water body, settlements and scrub lands were recognized and their impact on the environment has been discussed. Google earth historical imagery during 2010 and 2017 are used to map and assess these land use and land cover changes in the ArcGIS flat form. LULC change detection analysis data showed that cropland, water bodies and scrublands were decreased by 10, 2, 14 and 20 percent, respectively from 2010 to 2017. On the other hand industrial areas and agricultural plantations showed an increasing trend with 14 and 20 percent growth rate respectively.

In the present investigation, a low-cost fermentation medium was designed to achieve the maximum production of lactase from the Bacillus sp. VUVD101 strain through the screening of different nutritional and physical variables, using the Plackett-Burman design. Fourteen variables of the fermentation process were selected: incubation time, temperature, pH, RPM, DO, inoculum size, inoculum age, MgSO4, l-Cysteine, KH2PO4, CaCl2, K2PHO4, corn steep liquor and lactose. The selected variables were evaluated through statistical analysis, based on their significance, coefficient value and standard effect plot. The results suggested that six variables, namely, corn steep liquor, lactose, MgSO4, temperature, pH and RPM, had influence with high confidence levels, while the remaining eight variables did not show a significant effect on production. The analysis of the variance value R2 (0.96) also showed the model used for prediction to be significant (p less than 0.05). The plot for the standard effect for each component and its traits provided accurate data by which to select well-suited variables for further optimization. In comparison with the basal medium, 68% higher enzyme activity was achieved from the model of the optimized medium, and lactase activity was found to be 18.31 U/ml. Keywords: Lactase, Variables, Nutrient sources, Plackett-Burman design