Recent Submissions

  • Heteroatom-Mediated Interactions between Ruthenium Single Atoms and an MXene Support for Efficient Hydrogen Evolution

    Ramalingam, Vinoth; Varadhan, Purushothaman; Fu, Hui-Chun; Kim, Hyunho; Zhang, Daliang; Chen, Shuangming; Song, Li; MA, Ding; Wang, Yun; Alshareef, Husam N.; He, Jr-Hau (Advanced Materials, Wiley, 2019-10-17) [Article]
    A titanium carbide (Ti3C2Tx) MXene is employed as an efficient solid support to host a nitrogen (N) and sulfur (S) coordinated ruthenium single atom (RuSA) catalyst, which displays superior activity toward the hydrogen evolution reaction (HER). X-ray absorption fine structure spectroscopy and aberration corrected scanning transmission electron microscopy reveal the atomic dispersion of Ru on the Ti3C2Tx MXene support and the successful coordination of RuSA with the N and S species on the Ti3C2Tx MXene. The resultant RuSA-N-S-Ti3C2Tx catalyst exhibits a low overpotential of 76 mV to achieve the current density of 10 mA cm−2. Furthermore, it is shown that integrating the RuSA-N-S-Ti3C2Tx catalyst on n+np+-Si photocathode enables photoelectrochemical hydrogen production with exceptionally high photocurrent density of 37.6 mA cm−2 that is higher than the reported precious Pt and other noble metals catalysts coupled to Si photocathodes. Density functional theory calculations suggest that RuSA coordinated with N and S sites on the Ti3C2Tx MXene support is the origin of this enhanced HER activity. This work would extend the possibility of using the MXene family as a solid support for the rational design of various single atom catalysts.
  • High-speed colour-converting photodetector with all-inorganic CsPbBr3 perovskite nanocrystals for ultraviolet light communication

    Kang, Chun Hong; Dursun, Ibrahim; Liu, Guangyu; Sinatra, Lutfan; Sun, Xiaobin; Kong, Meiwei; Pan, Jun; Maity, Partha; Ooi, Ee-Ning; Ng, Tien Khee; Mohammed, Omar F.; Bakr, Osman; Ooi, Boon S. (Light: Science & Applications, Springer Science and Business Media LLC, 2019-10-16) [Article]
    Optical wireless communication (OWC) using the ultra-broad spectrum of the visible-to-ultraviolet (UV) wavelength region remains a vital field of research for mitigating the saturated bandwidth of radio-frequency (RF) communication. However, the lack of an efficient UV photodetection methodology hinders the development of UV-based communication. The key technological impediment is related to the low UV-photon absorption in existing silicon photodetectors, which offer low-cost and mature platforms. To address this technology gap, we report a hybrid Si-based photodetection scheme by incorporating CsPbBr3 perovskite nanocrystals (NCs) with a high photoluminescence quantum yield (PLQY) and a fast photoluminescence (PL) decay time as a UV-to-visible colour-converting layer for high-speed solar-blind UV communication. The facile formation of drop-cast CsPbBr3 perovskite NCs leads to a high PLQY of up to ~73% and strong absorption in the UV region. With the addition of the NC layer, a nearly threefold improvement in the responsivity and an increase of ~25% in the external quantum efficiency (EQE) of the solar-blind region compared to a commercial silicon-based photodetector were observed. Moreover, time-resolved photoluminescence measurements demonstrated a decay time of 4.5 ns under a 372-nm UV excitation source, thus elucidating the potential of this layer as a fast colour-converting layer. A high data rate of up to 34 Mbps in solar-blind communication was achieved using the hybrid CsPbBr3–silicon photodetection scheme in conjunction with a 278-nm UVC light-emitting diode (LED). These findings demonstrate the feasibility of an integrated high-speed photoreceiver design of a composition-tuneable perovskite-based phosphor and a low-cost silicon-based photodetector for UV communication.
  • A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells.

    Cali, Corrado; Kare, Kalpana; Agus, Marco; Veloz Castillo, Maria Fernanda; Boges, Daniya; Hadwiger, Markus; Magistretti, Pierre J. (Journal of visualized experiments : JoVE, MyJove Corporation, 2019-10-15) [Article]
    Serial sectioning and subsequent high-resolution imaging of biological tissue using electron microscopy (EM) allow for the segmentation and reconstruction of high-resolution imaged stacks to reveal ultrastructural patterns that could not be resolved using 2D images. Indeed, the latter might lead to a misinterpretation of morphologies, like in the case of mitochondria; the use of 3D models is, therefore, more and more common and applied to the formulation of morphology-based functional hypotheses. To date, the use of 3D models generated from light or electron image stacks makes qualitative, visual assessments, as well as quantification, more convenient to be performed directly in 3D. As these models are often extremely complex, a virtual reality environment is also important to be set up to overcome occlusion and to take full advantage of the 3D structure. Here, a step-by-step guide from image segmentation to reconstruction and analysis is described in detail.
  • More efficient time integration for Fourier pseudo-spectral DNS of incompressible turbulence

    Ketcheson, David I.; Mortensen, Mikael; Parsani, Matteo; Schilling, Nathanael (International Journal for Numerical Methods in Fluids, Wiley, 2019-10-15) [Article]
    Time integration of Fourier pseudo-spectral DNS is usually performed using the classical fourth-order accurate Runge–Kutta method, or other methods of second or third order, with a fixed step size. We investigate the use of higher-order Runge–Kutta pairs and automatic step size control based on local error estimation. We find that the fifth-order accurate Runge–Kutta pair of Bogacki & Shampine gives much greater accuracy at a significantly reduced computational cost. Specifically, we demonstrate speedups of 2x-10x for the same accuracy. Numerical tests (including the Taylor–Green vortex, Rayleigh–Taylor instability, and homogeneous isotropic turbulence) confirm the reliability and efficiency of the method. We also show that adaptive time stepping provides a significant computational advantage for some problems (like the development of a Rayleigh–Taylor instability) without compromising accuracy.
  • Low-Power Hardware Implementation of a Support Vector Machine Training and Classification for Neural Seizure Detection

    Elhosary, Heba; Zakhari, Michael H.; ElGammal, Mohamed A.; Elghany, Mohamed Abd; Salama, Khaled N.; Mostafa, Hassan (IEEE Transactions on Biomedical Circuits and Systems, IEEE, 2019-10-14) [Article]
    In this paper, a low power support vector machine (SVM) training, feature extraction, and classification algorithm are hardware implemented in a neural seizure detection application. The training algorithm used is the sequential minimal optimization (SMO) algorithm. The system is implemented on different platforms: such as field programmable gate array (FPGA), Xilinx Virtex-7 and application specific integrated circuit (ASIC) using hardware-calibrated UMC 65nm CMOS technology. The implemented training hardware is introduced as an accelerator intellectual property (IP), especially in the case of large number of training sets, such as neural seizure detection. Feature extraction and classification blocks are implemented to achieve the best trade-off between sensitivity and power consumption. The proposed seizure detection system achieves a sensitivity around 96.77% when tested with the implemented linear kernel classifier. A power consumption evaluation is performed on both the ASIC and FPGA platforms showing that the ASIC power consumption is improved by a factor of 2X when compared with the FPGA counterpart.
  • Stochastic Geometry-based analysis of Airborne Base Stations with Laser-powered UAVs

    Lahmeri, Mohamed-Amine; Kishk, Mustafa Abdelsalam; Alouini, Mohamed-Slim (IEEE Communications Letters, IEEE, 2019-10-11) [Article]
    One of the most promising solutions to the problem of limited flight time of unmanned aerial vehicles (UAVs), is providing the UAVs with power through laser beams emitted from Laser Beam Directors (LBDs) deployed on the ground. In this letter, we study the performance of a laser-powered UAV-enabled communication system using tools from stochastic geometry. We first derive the energy coverage probability, which is defined as the probability of the UAV receiving enough energy to ensure successful operation (hovering and communication). Our results show that to ensure energy coverage, the distance between the UAV and its dedicated LBD must be below a certain threshold, for which we derive an expression as a function of the system parameters. Considering simultaneous information and power transmission through the laser beam using power splitting technique, we also derive the joint energy and the Signal-to-noise Ratio (SNR) coverage probability. The analytical and simulation results reveal some interesting insights. For instance, our results show that we need at least 6 LBDs/10km2 to ensure a reliable performance in terms of energy coverage probability.
  • An explicit marching-on-in-time scheme for solving the time domain Kirchhoff integral equation.

    Chen, Rui; Sayed, Sadeed B; Al-Harthi, Noha A.; Keyes, David E.; Bagci, Hakan (The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), 2019-10-09) [Article]
    A fully explicit marching-on-in-time (MOT) scheme for solving the time domain Kirchhoff (surface) integral equation to analyze transient acoustic scattering from rigid objects is presented. A higher-order Nyström method and a PE(CE)m-type ordinary differential equation integrator are used for spatial discretization and time marching, respectively. The resulting MOT scheme uses the same time step size as its implicit counterpart (which also uses Nyström method in space) without sacrificing from the accuracy and stability of the solution. Numerical results demonstrate the accuracy, efficiency, and applicability of the proposed explicit MOT solver.
  • Novel algorithms for efficient subsequence searching and mapping in nanopore raw signals towards targeted sequencing.

    Han, Renmin; wang, sheng; Gao, Xin (Bioinformatics (Oxford, England), Oxford University Press (OUP), 2019-10-09) [Article]
    MOTIVATION:Genome diagnostics have gradually become a prevailing routine for human healthcare. With the advances in understanding the causal genes for many human diseases, targeted sequencing provides a rapid, cost-efficient and focused option for clinical applications, such as SNP detection and haplotype classification, in a specific genomic region. Although nanopore sequencing offers a perfect tool for targeted sequencing because of its mobility, PCR-freeness, and long read properties, it poses a challenging computational problem of how to efficiently and accurately search and map genomic subsequences of interest in a pool of nanopore reads (or raw signals). Due to its relatively low sequencing accuracy, there is no reliable solution to this problem, especially at low sequencing coverage. RESULTS:Here, we propose a brand new signal-based subsequence inquiry pipeline as well as two novel algorithms to tackle this problem. The proposed algorithms follow the principle of subsequence dynamic time warping and directly operate on the electrical current signals, without loss of information in base-calling. Therefore, the proposed algorithms can serve as a tool for sequence inquiry in targeted sequencing. Two novel criteria are offered for the consequent signal quality analysis and data classification. Comprehensive experiments on real-world nanopore datasets show the efficiency and effectiveness of the proposed algorithms. We further demonstrate the potential applications of the proposed algorithms in two typical tasks in nanopore-based targeted sequencing: SNP detection under low sequencing coverage, and haplotype classification under low sequencing accuracy. AVAILABILITY:The project is accessible at https://github.com/icthrm/cwSDTWnano.git, and the presented bench data is available upon request.
  • An explicit marching-on-in-time scheme for solving the time domain Kirchhoff integral equation.

    Chen, Rui; Sayed, Sadeed B; Al-Harthi, Noha A.; Keyes, David E.; Bagci, Hakan (The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), 2019-10-09) [Article]
    A fully explicit marching-on-in-time (MOT) scheme for solving the time domain Kirchhoff (surface) integral equation to analyze transient acoustic scattering from rigid objects is presented. A higher-order Nyström method and a PE(CE)m-type ordinary differential equation integrator are used for spatial discretization and time marching, respectively. The resulting MOT scheme uses the same time step size as its implicit counterpart (which also uses Nyström method in space) without sacrificing from the accuracy and stability of the solution. Numerical results demonstrate the accuracy, efficiency, and applicability of the proposed explicit MOT solver.
  • Wind power prediction using bootstrap aggregating trees approach to enabling sustainable wind power integration in a smart grid

    Harrou, Fouzi; Saidi, Ahmed; Sun, Ying (Energy Conversion and Management, Elsevier BV, 2019-10-09) [Article]
    Precise prediction of wind power is important in sustainably integrating the wind power in a smart grid. The need for short-term predictions is increased with the increasing installed capacity. The main contribution of this work is adopting bagging ensembles of decision trees approach for wind power prediction. The choice of this regression approach is motivated by its ability to take advantage of many relatively weak single trees to reach a high prediction performance compared to single regressors. Moreover, it reduces the overall error and has the capacity to merge numerous models. The performance of bagged trees for predicting wind power has been compared to four commonly know prediction methods namely multivariate linear regression, support vector regression, principal component regression, and partial least squares regression. Real measurements recorded every ten minutes from an actual wind turbine are used to illustrate the prediction quality of the studied methods. Results showed that the bagged trees regression approach reached the highest prediction performance with a coefficient of determination of 0.982. The result showed that the bagged trees approach is followed by support vector regression with Gaussian kernel, the same model when using a quadratic kernel, and the multivariate linear regression, partial least squares, and principal component regression gave the lowest prediction. The investigated models in this study can represent a helpful tool for model-based anomaly detection in wind turbines.
  • Ultraviolet-to-blue color-converting scintillating-fibers photoreceiver for 375-nm laser-based underwater wireless optical communication

    Kang, Chun Hong; Trichili, Abderrahmen; Alkhazragi, Omar; Zhang, Huafan; Subedi, Ram Chandra; Guo, Yujian; Mitra, Somak; Shen, Chao; Roqan, Iman S.; Ng, Tien Khee; Alouini, Mohamed-Slim; Ooi, Boon S. (Optics Express, The Optical Society, 2019-10-08) [Article]
    Underwater wireless optical communication (UWOC) can offer reliable and secure connectivity for enabling future internet-of-underwater-things (IoUT), owing to its unlicensed spectrum and high transmission speed. However, a critical bottleneck lies in the strict requirement of pointing, acquisition, and tracking (PAT), for effective recovery of modulated optical signals at the receiver end. A large-area, high bandwidth, and wide-angle-of-view photoreceiver is therefore crucial for establishing a high-speed yet reliable communication link under non-directional pointing in a turbulent underwater environment. In this work, we demonstrated a large-area, of up to a few tens of cm2, photoreceiver design based on ultraviolet(UV)-to-blue color-converting plastic scintillating fibers, and yet offering high 3-dB bandwidth of up to 86.13 MHz. Tapping on the large modulation bandwidth, we demonstrated a high data rate of 250 Mbps at bit-error ratio (BER) of 2.2 × 10−3 using non-return-to-zero on-off keying (NRZ-OOK) pseudorandom binary sequence (PRBS) 210-1 data stream, a 375-nm laser-based communication link over the 1.15-m water channel. This proof-of-concept demonstration opens the pathway for revolutionizing the photodetection scheme in UWOC, and for non-line-of-sight (NLOS) free-space optical communication.
  • End-to-end Performance Analysis of Delay-sensitive Multi-relay Networks

    Makki, Behrooz; Alouini, Mohamed-Slim (IEEE Communications Letters, IEEE, 2019-10-07) [Article]
    We study the end-to-end (E2E) performance of multi-relay networks in delay-constrained applications. The results are presented for both decode-and-forward (DF) and AF (A: amplify) relaying schemes. We use some fundamental results on the achievable rates of finite-length codes to analyze the system performance in the cases with short packets. Taking the message decoding delays and different numbers of hops into account, we derive closed-form expressions for the E2E packet transmission delay, the E2E error probability as well as the E2E throughput. Moreover, for different message decoding delays, we determine the appropriate codeword length and the relay power such that the same E2E error probability and packet transmission delay are achieved in the AF-and DF-relay networks. As we show, for different codeword lengths and numbers of hops, the E2E performance of multi-relay networks are affected by the message decoding delay of the nodes considerably.
  • A Novel Subdomain 2D/Q-2D Finite Element Method for Power/Ground Plate-Pair Analysis

    Li, Ping; Jiang, Li Jun; Tang, Min; Zhang, Yao Jiang; Xu, Shuai; Bagci, Hakan (IEEE Transactions on Electromagnetic Compatibility, IEEE, 2019-10-07) [Article]
    Upon excitation by a surface magnetic current, a power/ground plate-pair supports only $\mathrm{TM}^{z}$ modes. This means that the magnetic field has only azimuthal components permitting a simple but effective domain decomposition method (DDM) to be used. In the proximity of an antipad, field interactions are rigorously modeled by a quasi-two-dimensional (Q-2D) finite element method (FEM) making use of three-dimensional (3D) triangular prism mesh elements. Since high-order $\mathrm{TM}^{z}$ modes are confined in the close proximity of the antipad, field interactions in the region away from the antipad only involve the fundamental mode and are rigorously modeled by a 2D FEM. This approach reduces 3D computation domain into a hybrid 2D/Q-2D domain. The discretization of this hybrid domain results in a global matrix system consisting of two globally coupled matrix equations pertinent to 2D and Q-2D domains. In this article, these two matrix equations are “decoupled” using a Riemann solver and the information exchange between the two domains is facilitated using numerical flux. The resulting decoupled two matrix equations are iteratively solved using the Gauss–Seidel algorithm. The accuracy, efficiency, and robustness of the proposed DDM are verified by four representative examples.
  • Proteome-level assessment of origin, prevalence and function of Leucine-Aspartic Acid (LD) motifs.

    Alam, Tanvir; Alazmi, Meshari; Naser, Rayan Mohammad Mahmoud; Huser, Franceline; Momin, Afaque Ahmad Imtiyaz; Astro, Veronica; Hong, Seungbeom; Walkiewicz, Katarzyna Wiktoria; Canlas, Christian G; Huser, Raphaël; Ali, Amal J.; Merzaban, Jasmeen; Adamo, Antonio; Jaremko, Mariusz; Jaremko, Lukasz; Bajic, Vladimir B.; Gao, Xin; Arold, Stefan T. (Bioinformatics (Oxford, England), Oxford University Press (OUP), 2019-10-05) [Article]
    MOTIVATION:Leucine-aspartic acid (LD) motifs are short linear interaction motifs (SLiMs) that link paxillin family proteins to factors controlling cell adhesion, motility and survival. The existence and importance of LD motifs beyond the paxillin family is poorly understood. RESULTS:To enable a proteome-wide assessment of LD motifs, we developed an active-learning based framework (LDmotif finder; LDMF) that iteratively integrates computational predictions with experimental validation. Our analysis of the human proteome revealed a dozen new proteins containing LD motifs. We found that LD motif signalling evolved in unicellular eukaryotes more than 800 Myr ago, with paxillin and vinculin as core constituents, and nuclear export signal (NES) as a likely source of de novo LD motifs. We show that LD motif proteins form a functionally homogenous group, all being involved in cell morphogenesis and adhesion. This functional focus is recapitulated in cells by GFP-fused LD motifs, suggesting that it is intrinsic to the LD motif sequence, possibly through their effect on binding partners. Our approach elucidated the origin and dynamic adaptations of an ancestral SLiM, and can serve as a guide for the identification of other SLiMs for which only few representatives are known. AVAILABILITY:LDMF is freely available online at www.cbrc.kaust.edu.sa/ldmf; Source code is available at https://github.com/tanviralambd/LD/. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.
  • Modeling and Experimental Study of the Vibration Effects in Urban Free-Space Optical Communication Systems

    Cai, Wenqi; Ndoye, Ibrahima; Ooi, Boon S.; Alouini, Mohamed-Slim; Laleg-Kirati, Taous-Meriem (IEEE Photonics Journal, IEEE, 2019-10-04) [Article]
    Free-space optical (FSO) communication, considered as a last-mile technology, is widely used in many urban scenarios. However, the performance of urban free-space optical (UFSO) communication systems fades in the presence of system vibration caused by many factors in the chaotic urban environment. In this paper, we develop a dedicated indoor vibration platform and atmospheric turbulence to estimate the Bifurcated-Gaussian (B-G) distribution model of the receiver optical power under different vibration levels and link distances using nonlinear iteration method. Mean square error (MSE) and coefficient of determination ($R^2$) metrics have been used to show a good agreement between the PDFs of the experimental data with the resulting B-G distribution model. Besides, the UFSO channel under the effects of both vibration and atmospheric turbulence is also explored under three atmospheric turbulence conditions. Our proposed B-G distribution model describes the vibrating UFSO channels properly and can easily help to perform and evaluate the link performance of UFSO systems, e.g., bit-error-rate (BER), outage probability. Furthermore, this work paves the way for constructing completed auxiliary control subsystems for robust UFSO links and contributes to more extensive optical communication scenarios, such as underwater optical communication, etc.
  • Tunable Dual-Wavelength Self-injection Locked InGaN/GaN Green Laser Diode

    Shamim, Md. Hosne Mobarok; Alkhazragi, Omar; Ng, Tien Khee; Ooi, Boon S.; Khan, Mohammed Zahed Mustafa (IEEE Access, Institute of Electrical and Electronics Engineers (IEEE), 2019-10-01) [Article]
    We implemented a tunable dual-longitudinal-mode spacing InGaN/GaN green (521–528 nm) laser diode by employing a self-injection locking scheme that is based on an external cavity configuration and utilizing either a high-or partial-reflecting mirror. A tunable longitudinal-mode spacing of 0.20 – 5.96 nm was accomplished, corresponding to a calculated frequency difference of 0.22–6.51 THz, as a result. The influence of operating current and temperature on the system performance was also investigated with a measured maximum side-mode-suppression ratio of 30.4 dB and minimum dual-mode peak optical power ratio of 0.03 dB. To shed light on the operation of the dual-wavelength device arising from the tunable longitudinal-mode spacing mechanism, the underlying physics is qualitatively described. To the best of our knowledge, this tunable longitudinal-mode-spacing dual-wavelength device is novel, and has potential applications as an alternative means in millimeter wave and THz generation, thus possibly addressing the terahertz technology gap. The dual-wavelength operation is also attractive for high-resolution imaging and broadband wireless communication.
  • CDPath: Cooperative driver pathways discovery using integer linear programming and Markov clustering

    Yang, Ziying; Yu, Guoxian; Guo, Maozu; Yu, Jiantao; Zhang, Xiangliang; Wang, Jun (IEEE/ACM Transactions on Computational Biology and Bioinformatics, Institute of Electrical and Electronics Engineers (IEEE), 2019-10-01) [Article]
    Discovering driver pathways is an essential task to understand the pathogenesis of cancer and to design precise treatments for cancer patients. Increasing evidences have been indicating that multiple pathways often function cooperatively in carcinogenesis. In this study, we propose an approach called CDPath to discover cooperative driver pathways. CDPath firstly uses Integer Linear Programming to explore driver core modules from mutation profiles by enforcing co-occurrence and functional interaction relations between modules, and by maximizing the mutual exclusivity and coverage within modules. Next, to enforce cooperation of pathways and help the follow-up exact cooperative driver pathways discovery, it performs Markov clustering on pathway-pathway interaction network to cluster pathways. After that, it identifies pathways in different modules but in the same clusters as cooperative driver pathways. We apply CDPath on two TCGA datasets: breast cancer (BRCA) and endometrial cancer (UCEC). The results show that CDPath can identify known (i.e., TP53) and potential driver genes (i.e., SPTBN2). In addition, the identified cooperative driver pathways are related with the target cancer, and they are involved with carcinogenesis and several key biological processes. CDPath can uncover more potential biological associations between pathways (over 100%) and more cooperative driver pathways (over 200%) than competitive approaches.
  • CDPath: Cooperative driver pathways discovery using integer linear programming and Markov clustering

    Yang, Ziying; Yu, Guoxian; Guo, Maozu; Yu, Jiantao; Zhang, Xiangliang; Wang, Jun (IEEE/ACM Transactions on Computational Biology and Bioinformatics, Institute of Electrical and Electronics Engineers (IEEE), 2019-10-01) [Article]
    Discovering driver pathways is an essential task to understand the pathogenesis of cancer and to design precise treatments for cancer patients. Increasing evidences have been indicating that multiple pathways often function cooperatively in carcinogenesis. In this study, we propose an approach called CDPath to discover cooperative driver pathways. CDPath firstly uses Integer Linear Programming to explore driver core modules from mutation profiles by enforcing co-occurrence and functional interaction relations between modules, and by maximizing the mutual exclusivity and coverage within modules. Next, to enforce cooperation of pathways and help the follow-up exact cooperative driver pathways discovery, it performs Markov clustering on pathway-pathway interaction network to cluster pathways. After that, it identifies pathways in different modules but in the same clusters as cooperative driver pathways. We apply CDPath on two TCGA datasets: breast cancer (BRCA) and endometrial cancer (UCEC). The results show that CDPath can identify known (i.e., TP53) and potential driver genes (i.e., SPTBN2). In addition, the identified cooperative driver pathways are related with the target cancer, and they are involved with carcinogenesis and several key biological processes. CDPath can uncover more potential biological associations between pathways (over 100%) and more cooperative driver pathways (over 200%) than competitive approaches.
  • Computer-aided drug repurposing for cancer therapy: Approaches and opportunities to challenge anticancer targets.

    Mottini, Carla; Napolitano, Francesco; Li, Zhongxiao; Gao, Xin; Cardone, Luca (Seminars in cancer biology, Elsevier BV, 2019-09-29) [Article]
    Despite huge efforts made in academic and pharmaceutical worldwide research, current anticancer therapies achieve effective treatment in a limited number of neoplasia cases only. Oncology terms such as big killers - to identify tumours with yet a high mortality rate - or undruggable cancer targets, and chemoresistance, represent the current therapeutic debacle of cancer treatments. In addition, metastases, tumour microenvironments, tumour heterogeneity, metabolic adaptations, and immunotherapy resistance are essential features controlling tumour response to therapies, but still, lack effective therapeutics or modulators. In this scenario, where the pharmaceutical productivity and drug efficacy in oncology seem to have reached a plateau, the so-called drug repurposing - i.e. the use of old drugs, already in clinical use, for a different therapeutic indication - is an appealing strategy to improve cancer therapy. Opportunities for drug repurposing are often based on occasional observations or on time-consuming pre-clinical drug screenings that are often not hypothesis-driven. In contrast, in-silico drug repurposing is an emerging, hypothesis-driven approach that takes advantage of the use of big-data. Indeed, the extensive use of -omics technologies, improved data storage, data meaning, machine learning algorithms, and computational modeling all offer unprecedented knowledge of the biological mechanisms of cancers and drugs' modes of action, providing extensive availability for both disease-related data and drugs-related data. This offers the opportunity to generate, with time and cost-effective approaches, computational drug networks to predict, in-silico, the efficacy of approved drugs against relevant cancer targets, as well as to select better responder patients or disease' biomarkers. Here, we will review selected disease-related data together with computational tools to be exploited for the in-silico repurposing of drugs against validated targets in cancer therapies, focusing on the oncogenic signaling pathways activation in cancer. We will discuss how in-silico drug repurposing has the promise to shortly improve our arsenal of anticancer drugs and, likely, overcome certain limitations of modern cancer therapies against old and new therapeutic targets in oncology.
  • Error Rate Analysis of Amplitude-Coherent Detection over Rician Fading Channels with Receiver Diversity

    Al-Jarrah, Mohammad; Park, Kihong; Al-Dweik, Arafat; Alouini, Mohamed-Slim (IEEE Transactions on Wireless Communications, Institute of Electrical and Electronics Engineers (IEEE), 2019-09-27) [Article]
    Amplitude-coherent (AC) detection is an efficient technique that can simplify the receiver design while providing reliable symbol error rate (SER). Therefore, this work considers AC detector design and SER analysis using M-ary amplitude shift keying (MASK) modulation with receiver diversity over Rician fading channels. More specifically, we derive the optimum, near-optimum and a suboptimum AC detectors and compare their SER with the coherent, phase-coherent, noncoherent and the heuristic AC detectors. Moreover, the analytical and asymptotic SER at high signal-to-noise ratios (SNRs) are derived for the heuristic detector using single and multiple receiving antennas. The obtained analytical and simulation results show that the SER of the AC and coherent MASK detectors are comparable, particularly for high values of the Rician K-factor, and small number of receiving antennas. In most of the considered scenarios, the heuristic AC detector outperforms the optimum noncoherent detector significantly, except for the binary ASK case at low SNRs. Moreover, the obtained results show that the heuristic AC detector is immune to phase noise, and thus, it outperforms the coherent detector in scenarios where the system is subject to considerable phase noise.

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