Recent Submissions

  • Interaction of tetrameric and dimeric FBP2 with CAMK2α, HIF1α and ALDOA

    Budziak, Bartosz (2022-08-06) [Poster]
    Macromolecular interactions are common mechanisms of protein function regulation. Emerging role of muscle fructose 1,6-bisphospatase (FBP2) in memory formation and cancer cells survival was hypothesized to be regulated by such interactions. FBP2 exists as mixture of different oligomeric states which presumably may interact with their binding partners in a different mode. Results presented here show how alterations of FBP2 quaternary structure affects interactions with such proteins as CAMK2?, HIF1? or ALDOA. We show that a dimeric FBP2 is preferred form of the enzyme for interaction with CAMK2?. On the other hand, an inactive tetrameric T-state of FBP2 binds HIF1? and, to a lesser extent, ALDOA stronger than the dimeric and an active R-state tetrameric FBP2.
  • Untargeted Metabolomic Profiling and Antioxidant Capacities of Different Solvent Crude Extracts of Ephedra foeminea

    Al-Nemi, Ruba (2022-08-06) [Poster]
    This study aims to investigate the chemical profiles of different solvent (Ace, acetone; DCM/MeOH, dichloromethane/methanol; EtOH, ethanol; EA, ethyl acetate; MeOH, methanol) extracts of Ephedra foeminea collected from Jordan via an untargeted metabolomics approach using NMR, GC-MS, LCMS and analyzing the data through Venn diagrams, PCA plots, and Metabolite Set Enrichment Analysis (MESA), while determining their antioxidant capacities using ABTS assays. Results revealed the dominant chemical groups as amino acids, fatty acids, carboxylic acids, and carbohydrates, it was also found that the DCM/MeOH and MeOH extracts had the most distinct composition and most unique compounds. The methanolic extract was relatively the most potent in the ABTS assay (IC50 249.6 µg/mL). In conclusion, solvents influenced the recovery of metabolites in E. foeminea and the antioxidant activity of the E. foeminea methanolic extract could be correlated to the abundant presence of diverse bioactive compounds.
  • A new R package for evaluation of probabilistic forecasts based on locally scale invariant proper scoring rules

    Alghanem, Abdulaziz (2022-08-02) [Poster]
    It is common to make predictions in the form of probabilistic forecasts in areas such as weather forecasting. Proper scoring rules are the standard way to evaluate these predictions. We implement a newly proposed proper scoring rule, which has some desirable properties, in an R package. We then use it to compare different fitted models with real data.
  • Fast Data Transfer to Mitigate Data Stall in Machine Learning Models

    Saigal, Manar (2022-08-02) [Poster]
    Deep Neural Network (DNN) is one of the most influential models that provides promising machine learning solutions. However, DNN training consumes much data, energy, and time. It is also resource-intensive as its data pipeline stages start from storage through to the CPU and end with the GPU. The first two stages involve fetching data from storage and implementing data pre-processing in the CPU, and they consume much time; this eventually leads to a data stall problem which describes leaving the GPU, in the third stage, waiting for data to be fetched or pre-processed in an idle state. To mitigate the data-stall problem in terms of pre-processing, we designed a distributed machine learning system that takes advantage of programmable in-network components to accelerate the processes and reduce the load on the CPU via pre-processing. In this project, an Alveo U280 Data Center Accelerator Card programmed with Verilog was used to perform the following common pre-processing transformations: One-hot, Clamp, Random Selection, Cartesian Product, and Timestamp.
  • Optimal Placement of Reconfigurable Intelligent Surfaces (RIS) for Wireless Systems

    Abalroos, Mohammed (2022-08-02) [Poster]
    Reconfigurable Intelligent Surfaces (RIS) have been proposed to reconfigure the wireless propagation environment and enhance transmission performance. A RIS is made of passive reconfigurable elements and can vary the phase and amplitude of the incident signals to reflect them in the desired directions. RISs do not require power-hungry RF chains and power amplifiers, making them low-cost and energy-efficient solutions for coverage extensions. RIS-aided communications can therefore be used to extend the coverage range of actual wireless networks. In our work, we study the optimal placement of RISs for wireless systems, considering the existence of blockages in the terrain.
  • Revamping our wastewater treatment process with anaerobic membrane bioreactor (AnMBR) and hybrids: addressing global challenges

    Hong, Peiying (2022-08-02) [Poster]
    More than 50% of the global population lives in water-scarce areas. Reclaimed wastewater can be used to alleviate water scarcity. However, conventional wastewater processes incur high energy footprint and emit greenhouse gases when generating reclaimed water. More sustainable wastewater treatment alternatives are needed to produce high quality reclaimed water, hence addressing both water scarcity and climate change simultaneously.
  • The Deep Imaging Group at KAUST

    Ravasi, Matteo (2022-08-02) [Poster]
    The Deep Imaging Group is a research group in the Earth Science and Engineering School at KAUST working on many exciting geophysical problems. At DIG we aim to deepen the understanding of the subsurface, which will continue to be our main source of energy for the years to come, from clean gas resources to geothermal, all the way through to carbon storage. We do so by contributing to the development of processing, imaging, and inversion geophysical algorithms which will help geoscientist to make more informed decisions. We believe that with the help of deep learning we can enrich some of our existing geophysical technologies and solve long-standing issues in the solution of very ill-conditioned inverse problem in a variety of geophysical and related applications.
  • Green and More Sustainable Desalination Technologies

    Ghaffour, Noreddine (2022-08-02) [Poster]
  • Customized mesoporous metal organic frameworks (MOFs) engender stable enzymatic nanoreactors

    Alsufyani, Yara (2022-08-02) [Poster]
    Synthesis and characterization of MIL-101(Fe) and its importance in the enzymatic field.
  • Abstract 924: Modelling the metastatic castration-resistant prostate cancer in mice by orthotopic delivering multiplexed gRNAs of CRISPR/Cas9 based on AAV system

    Cai, Huiqiang; Zhang, Bin; Ahrenfeldt, Johanne; Birkbak, Nicolai; Thomsen, Martin (American Association for Cancer Research (AACR), 2022-06-15) [Poster]
    Prostate cancer (PCa) is a most common cause of cancer-related death in men. While it develops to metastatic stage, the treatment options are limited. Hence, it desires in vivo models to test novel strategies for treating PCa. Current murine models of prostate cancer need long time for the diseases to progress to an invasive and metastatic cancer. Here, we combined AAV delivery and CRISPR-Cas9 technology to mutate several genes simultaneously in the mouse prostate. Four weeks after delivering of engineered virus, benign prostatic intraepithelial neoplasia (PIN) can be achieved and within eight weeks, the tumor developed to an extremely aggressive cancer. Surprisingly, a basic virus, engineering quintuple gRNAs of Cas9 including Pten, Trp53 and Rb1 induced a primary tumor without formation of metastasis. While adding triple gRNAs targeting epigenetic factors to the basic viral vector, all mice developed lung metastasis with metastasis started to appear after 6 weeks. Castration of the tumor baring mice 5 weeks after initiation did not alter primary tumor and metastasis formation, indicating the metastatic castration-resistant prostate cancer (mCRPC) nature of the model. To reveal the molecular mechanism for cancer progression and metastasis formation, whole genome sequencing (WGS) were performed on lung metastasis samples in combination with mRNA-seq on primary and secondary tumors from the two groups and PBS-injected mice control. Up to 5,000 mutations were accumulated in the genome, although the number varied across the metastatic samples, which were mainly due to chromosome 6 and 8 and revealed heterogeneity of the tumors. Among it, novel key mutations were identified, which will be addressed in the future. Tumor cell plasticity, including epithelial-mesenchymal transition and de-differentiation, were conformed. A short 100kb genomic window at mouse chr5 was captured and found to be sensitive to mutation status of an epigenetic factor. This window is highly conserved to a region at human chr4 and in vitro work confirm evolutionary preserved mechanism. Finally, p-Src/p-Lyn-cMyc related pathways showed clear difference between the two primary tumors with and without metastasis potency. Overall, our model of mCRPC can provide very diverse angles to the initiation and progression of prostate cancer. Furthermore, this model can be used to rapidly verify ideas and hypothesis regarding the mechanism behind the disease, and to test the treatment strategies in vivo in both pre-clinic studies and pharmacy field.
  • Mangrove crab gill as microbial ecological niche

    Yang, Xinyuan (2022-05-24) [Poster]

View more