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Current updates of CRISPR/Cas9-mediated genome editing and targeting within tumor cells:an innovative strategy of cancer management

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Cancer Communications 2022年第12期42卷 1257-1287页

作者： Khaled S.Allemailem Mohammed A Alsahli Ahmad Almatroudi Faris Alrumaihi Fahd Khaleefah Alkhaleefah arshad husain rahmani Amjad Ali Khan Department of Medical Laboratories College of Applied Medical SciencesQassim UniversityBuraydahSaudi Arabia Department of Laboratory and Blood Bank Al Rass General HospitalAl RassSaudi Arabia Department of Basic Health Sciences College of Applied Medical SciencesQassim UniversityBuraydahSaudi Arabia

Clustered regularly interspaced short palindromic repeats-associated protein(CRISPR/Cas9),an adaptive microbial immune system,has been exploited as a robust,accurate,efficient and programmable method for genome targeting and editing.This innovative and revolutionary technique can play a significant role in animal modeling,in vivo genome therapy,engineered cell therapy,cancer diagnosis and treatment.The CRISPR/Cas9 endonuclease system targets a specific genomic locus by single guide RNA(sgRNA),forming a heteroduplex with target DNA.The Streptococcus pyogenes Cas9/sgRNA:DNA complex reveals a bilobed architecture with target recognition and nuclease lobes.CRISPR/Cas9 assembly can be hijacked,and its nanoformulation can be engineered as a delivery system for different clinical utilizations.However,the efficient and safe delivery of the CRISPR/Cas9 system to target tissues and cancer cells is very challenging,limiting its clinical utilization.Viral delivery strategies of this system may have many advantages,but disadvantages such as immune system stimulation,tumor promotion risk and small insertion size outweigh these advantages.Thus,there is a desperate need to develop an efficient non-viral physical delivery system based on simple nanoformulations.The delivery strategies of CRISPR/Cas9 by a nanoparticle-based system have shown tremendous potential,such as easy and large-scale production,combination therapy,large insertion size and efficient in vivo applications.This review aims to provide in-depth updates on Streptococcus pyogenic CRISPR/Cas9 structure and its mechanistic understanding.In addition,the advances in its nanoformulation-based delivery systems,including lipid-based,polymeric structures and rigid NPs coupled to special ligands such as aptamers,TAT peptides and cell-penetrating peptides,are discussed.Furthermore,the clinical applications in different cancers,clinical trials and future prospects of CRISPR/Cas9 delivery and genome targeting are also discussed.

关键词： cancer clinical trials CRISPR/Cas9 genome editing mechanism nanoparticles structure

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An Optimal DPM Based Energy-Aware Task Scheduling for Performance Enhancement in Embedded MPSoC

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Computers, Materials & Continua 2023年第1期74卷 2097-2113页

作者： Hamayun Khan Irfan Ud Din arshad Ali Mohammad husain Department of Electrical Engineering Faculty of Engineering&Technology Superior University Lahore54000Pakistan Department of Computer Science Faculty of Computer Science&IT Superior University Lahore54000Pakistan Faculty of Computer and Information Systems Islamic University of MadinahAl Madinah Al Munawarah42351Saudi Arabia

Minimizing the energy consumption to increase the life span and performance of multiprocessor system on chip(MPSoC)has become an integral chip design issue for multiprocessor systems.The performance measurement of computational systems is changing with the advancement in technology.Due to shrinking and smaller chip size power densities onchip are increasing rapidly that increasing chip temperature in multi-core embedded technologies.The operating speed of the device decreases when power consumption reaches a threshold that causes a delay in complementary metal oxide semiconductor(CMOS)circuits because high on-chip temperature adversely affects the life span of the chip.In this paper an energy-aware dynamic power management technique based on energy aware earliest deadline first(EA-EDF)scheduling is proposed for improving the performance and reliability by reducing energy and power consumption in the system on chip(SOC).Dynamic power management(DPM)enables MPSOC to reduce power and energy consumption by adopting a suitable core configuration for task migration.Task migration avoids peak temperature values in the multicore system.High utilization factor(ui)on central processing unit(CPU)core consumes more energy and increases the temperature on-chip.Our technique switches the core bymigrating such task to a core that has less temperature and is in a low power state.The proposed EA-EDF scheduling technique migrates load on different cores to attain stability in temperature among multiple cores of the CPU and optimized the duration of the idle and sleep periods to enable the low-temperature core.The effectiveness of the EA-EDF approach reduces the utilization and energy consumption compared to other existing methods and works.The simulation results show the improvement in performance by optimizing 4.8%on u_(i) 9%,16%,23%and 25%at 520 MHz operating frequency as compared to other energy-aware techniques for MPSoCs when the least number of tasks is in running state and can schedule more tasks to make an energy-efficient

关键词： Dynamic power management dynamic voltage&frequency scaling dynamic thermal management multiprocessor system on chip complementary metal oxide semiconductor reliability

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Automatic Real-Time Medical Mask Detection Using Deep Learning to Fight COVID-19

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Computer Systems Science & Engineering 2022年第9期42卷 1181-1198页

作者： Mohammad Khalid Imam rahmani Fahmina Taranum Reshma Nikhat Md.Rashid Farooqi Mohammed arshad Khan College of Computing and Informatics Saudi Electronic UniversityRiyadhSaudi Arabia Computer Science and Engineering Department Muffakham Jah College of Engineering and TechnologyOsmania UniversityHyderabadTelanganaIndia Department of Commerce and Business Management Maulana Azad National Urdu UniversityHyderabadTelanganaIndia Department of Accountancy College of Administrative and Financial SciencesSaudi Electronic UniversityRiyadSaudi Arabia

The COVID-19 pandemic is a virus that has disastrous effects onhuman lives globally;still spreading like wildfire causing huge losses to humanityand economies. There is a need to follow few constraints like social distancingnorms, personal hygiene, and masking up to effectively control the virus spread.The proposal is to detect the face frame and confirm the faces are properly covered with masks. By applying the concepts of Deep learning, the results obtainedfor mask detection are found to be effective. The system is trained using4500 images to accurately judge and justify its accuracy. The aim is to developan algorithm to automatically detect a mask, but the approach does not facilitatethe percentage of improper usage. Accuracy levels are as low as 50% if the maskis improperly covered and an alert is raised for improper placement. It can be usedat traffic places and social gatherings for the prevention of virus transmission. Itworks by first locating the region of interest by creating a frame boundary, thenfacial points are picked up to detect and concentrate on specific features. Thetraining on the input images is performed using different epochs until the artificialface mask detection dataset is created. The system is implemented using TensorFlow with OpenCV and Python using a Jupyter Notebook simulation environment. The training dataset used is collected from a set of diverse open-sourcedatasets with filtered images available at Kaggle Medical Mask Dataset by Mikolaj Witkowski, Kera, and Prajna Bhandary. To simulate MobilNetV2 classifier isused to load and pre-process the image dataset for building a fully connectedhead. The objective is to assess the accuracy of the identification, measuringthe efficiency and effectiveness of algorithms for precision, recall, and F1 score.

关键词： COVID-19 pandemic convolution neural network deep learning face detection facemask detection global health machine learning

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Force Sensitive Resistors-Based Real-Time Posture Detection System Using Machine Learning Algorithms

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Computers, Materials & Continua 2023年第11期77卷 1795-1814页

作者： Arsal Javaid Areeb Abbas Jehangir arshad Mohammad Khalid Imam rahmani Sohaib Tahir Chauhdary Mujtaba Hussain Jaffery Abdulbasid S.Banga Department of Electrical and Computer Engineering COMSATS University IslamabadLahore CampusLahore54000Pakistan College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia Department of Electrical and Computer Engineering College of EngineeringDhofar UniversitySalalah211Oman

To detect the improper sitting posture of a person sitting on a chair,a posture detection system using machine learning classification has been proposed in this work.The addressed problem correlates to the third Sustainable Development Goal(SDG),ensuring healthy lives and promoting well-being for all ages,as specified by the World Health Organization(WHO).An improper sitting position can be fatal if one sits for a long time in the wrong position,and it can be dangerous for ulcers and lower spine discomfort.This novel study includes a practical implementation of a cushion consisting of a grid of 3×3 force-sensitive resistors(FSR)embedded to read the pressure of the person sitting on it.Additionally,the Body Mass Index(BMI)has been included to increase the resilience of the system across individual physical variances and to identify the incorrect postures(backward,front,left,and right-leaning)based on the five machine learning algorithms:ensemble boosted trees,ensemble bagged trees,ensemble subspace K-Nearest Neighbors(KNN),ensemble subspace discriminant,and ensemble RUSBoosted trees.The proposed arrangement is novel as existing works have only provided simulations without practical implementation,whereas we have implemented the proposed design in Simulink.The results validate the proposed sensor placements,and the machine learning(ML)model reaches a maximum accuracy of 99.99%,which considerably outperforms the existing works.The proposed concept is valuable as it makes it easier for people in workplaces or even at individual household levels to work for long periods without suffering from severe harmful effects from poor posture.

关键词： Posture detection FSR sensor machine learning real-time KNN

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Managing the Mass Effect: A Rare Case of Giant Ethmoid Sinus Osteoma with Orbital Extension—A Case Report

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International Journal of Otolaryngology and Head & Neck Surgery 2023年第4期12卷 279-286页

作者： Siti Hajar Noordiana Mohamed Hasshim Azuin Izzati arshad Abdul Fattah Abdul Wahab Salina husain Department of Otorhinolaryngology Universiti Kebangsaan Malaysia Kuala Lumpur Malaysia Department of Otorhinolaryngology Hospital Sungai Buloh Selangor Malaysia Department of Otorhinolaryngology Ara Damansara Medical Centre Selangor Malaysia

Background: Sinonasalosteomas are rare benign tumors that can cause clinical symptoms depending on their size and location. Osteomas are classified as giant osteomas when their size gets larger than three centimeters. In giant osteomas, severe symptoms and complications can occur if they expand into adjacent structures. Aim: In this case report, we highlight the diagnostic importance of CT scans of paranasal sinuses in diagnosing osteomas and the superiority of endoscopic surgery over an open approach in removing these benign tumors. Case Presentation: We report a rare case of giant ethmoidosteoma with extension to intraorbital facilities in 19 years old female which was causing a mass effect on the orbital space and discuss the appropriate management. Conclusion: Ethmoid sinus osteoma is asymptomatic until it increases in size producing a pressure effect on the eyes and sinusitis. CT imaging is the gold standard diagnostic modality. Surgical excision is the treatment of choice for ethmoid sinus osteoma. Due to the size of the lesion, endoscopic surgical excision is a less commonly employed modality, but it has advantages like earlier recovery and cosmetic benefits due to which it was the treatment employed in this case.

关键词： Giant Osteoma Ethmoid Sinus Paranasalosteoma Orbital Extension Case Report

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