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Tocilizumab in severe COVID-19-A randomized,double-blind,placebo-controlled trial

Infectious Medicine 2022年第2期1卷 88-94页

作者： Muhammad Irfan Malik Sardar Al Fareed Zafar Fabiha Qayyum Muna Malik Muhammad Sohaib Asghar Muhammad Junaid Tahir Ammarah Arshad Fatima Khalil Hafiza Shafia Naz Mudassar Aslam Jodat Saleem Abdul Aziz mustafa usman azhar Muhammad Naqash Zohaib Yousaf Postgraduate Medical Institute LahorePakistan Lahore General Hospital LahorePakistan Ameer-ud-Din Medical College LahorePakistan Dow University of Health Sciences-Ojha Campus KarachiPakistan Sheikh Zayed Medical College Rahim Yar KhanPakistan Hamad Medical Corporation DohaQatar

Background:The therapeutic effectiveness of interleukin-6 receptor inhibitor in critically ill hospitalized patients with coronavirus disease 2019(COVID-19)is uncertain.Methods:To evaluate the efficacy and safety of the outcome as recovery or death of tocilizumab for severe acute respiratory syndrome-coronavirus-2(SARS-CoV-2)infection,we conducted a randomized,double-blinded,placebo-controlled phase 2 trial in critically ill COVID-19 adult patients.The patients were randomly assigned in a 4:1 ratio to receive standard medical treatment plus the recommended dose of either tocilizumab or the placebo drug.Randomization was stratified.The primary outcome was the recovery or death after administration of tocilizumab or a placebo drug.The secondary outcomes were clinical recovery or worsening of the patients’symptoms and inflammatory markers and discharge from the hospital.Results:Of 190 patients included in this study,152 received tocilizumab,and 38 received a placebo.The duration of hospital stay of the interventional group was 12.9±9.2,while the placebo group had a more extended hospital stay(15.6±8.8).The mortality ratio for the primary outcome,ie,mortality or recovery in the tocilizumab group was 17.8%;p=0.58 by log-rank test).The mortality ratio in the placebo group was 76.3%;p=0.32 by log-rank test).The inflammatory markers in the tocilizumab group significantly declined by day 16 compared to the placebo group.Conclusions:The use of tocilizumab was associated with decreased mortality,earlier improvement of inflamma-tory markers,and reduced hospital stay in patients with severe COVID-19.

关键词： Inflammatory Infectious Immunosuppression COVID-19 Therapy Trial

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3D Kronecker Convolutional Feature Pyramid for Brain Tumor Semantic Segmentation in MR Imaging

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Computers, Materials & Continua 2023年第9期76卷 2861-2877页

作者： Kainat Nazir Tahir mustafa Madni Uzair Iqbal Janjua Umer Javed Muhammad Attique Khan usman Tariq Jae-Hyuk Cha Medical Imaging and Diagnostics Lab NCAIDepartment of Computer ScienceCOMSATS University IslamabadIslamabad44000Pakistan Department of Electrical and Computer Engineering COMSATS University IslamabadWah CampusWahPakistan Department of Computer Science HITEC UniversityTaxilaPakistan Department of Management Information Systems College of Business AdministrationPrince Sattam Bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea

Brain tumor significantly impacts the quality of life and changes everything for a patient and their loved ones.Diagnosing a brain tumor usually begins with magnetic resonance imaging(MRI).The manual brain tumor diagnosis from the MRO images always requires an expert radiologist.However,this process is time-consuming and costly.Therefore,a computerized technique is required for brain tumor detection in MRI images.Using the MRI,a novel mechanism of the three-dimensional(3D)Kronecker convolution feature pyramid(KCFP)is used to segment brain tumors,resolving the pixel loss and weak processing of multi-scale lesions.A single dilation rate was replaced with the 3D Kronecker convolution,while local feature learning was performed using the 3D Feature Selection(3DFSC).A 3D KCFP was added at the end of 3DFSC to resolve weak processing of multi-scale lesions,yielding efficient segmentation of brain tumors of different sizes.A 3D connected component analysis with a global threshold was used as a post-processing technique.The standard Multimodal Brain Tumor Segmentation 2020 dataset was used for model validation.Our 3D KCFP model performed exceptionally well compared to other benchmark schemes with a dice similarity coefficient of 0.90,0.80,and 0.84 for the whole tumor,enhancing tumor,and tumor core,respectively.Overall,the proposed model was efficient in brain tumor segmentation,which may facilitate medical practitioners for an appropriate diagnosis for future treatment planning.

关键词： Brain tumor segmentation connect component analysis deep learning kronecker convolution magnetic resonance imaging

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A Hybrid Attention-Based Residual Unet for Semantic Segmentation of Brain Tumor

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Computers, Materials & Continua 2023年第7期76卷 647-664页

作者： Wajiha Rahim Khan Tahir mustafa Madni Uzair Iqbal Janjua Umer Javed Muhammad Attique Khan Majed Alhaisoni usman Tariq Jae-Hyuk Cha Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Department of Electrical and Computer Engineering COMSATS University IslamabadWah CampusPakistan Department of Computer Science HITEC UniversityTaxilaPakistan Department of Computer Science College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Management Information Systems CoBAPrince Sattam Bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea

Segmenting brain tumors in Magnetic Resonance Imaging(MRI)volumes is challenging due to their diffuse and irregular shapes.Recently,2D and 3D deep neural networks have become famous for medical image segmentation because of the availability of labelled datasets.However,3D networks can be computationally expensive and require significant training resources.This research proposes a 3D deep learning model for brain tumor segmentation that uses lightweight feature extraction modules to improve performance without compromising contextual information or accuracy.The proposed model,called Hybrid Attention-Based Residual Unet(HA-RUnet),is based on the Unet architecture and utilizes residual blocks to extract low-and high-level features from MRI volumes.Attention and Squeeze-Excitation(SE)modules are also integrated at different levels to learn attention-aware features adaptively within local and global receptive fields.The proposed model was trained on the BraTS-2020 dataset and achieved a dice score of 0.867,0.813,and 0.787,as well as a sensitivity of 0.93,0.88,and 0.83 for Whole Tumor,Tumor Core,and Enhancing Tumor,on test dataset respectively.Experimental results show that the proposed HA-RUnet model outperforms the ResUnet and AResUnet base models while having a smaller number of parameters than other state-of-the-art models.Overall,the proposed HA-RUnet model can improve brain tumor segmentation accuracy and facilitate appropriate diagnosis and treatment planning for medical practitioners.

关键词： MRI volumes residual Unet BraTs-2020 squeeze-excitation(SE)

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Structural and optical properties of thermally reduced graphene oxide for energy devices

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Chinese Physics B 2017年第8期26卷 346-352页

作者： Ayesha Jamil Faiza mustafa Samia Aslam usman Arshad Muhammad Ashfaq Ahmad Department of Physics COMSATS Institute of Information TechnologyLahore 54000Pakistan

Natural intercalation of the graphite oxide, obtained as a product of Hummer＇s method, via ultra-sonication of water dispersed graphite oxide has been carried out to obtain graphene oxide（GO） and thermally reduced graphene oxide（RGO）.Here we report the effect of metallic nitrate on the oxidation properties of graphite and then formation of metallic oxide（MO） composites with GO and RGO for the first time. We observed a change in the efficiency of the oxidation process as we replaced the conventionally used sodium nitrate with that of nickel nitrate Ni（NO_3）_2, cadmium nitrate Cd（NO_3）_2,and zinc nitrate Zn（NO_3）_2. The structural properties were investigated by x-ray diffraction and observed the successful formation of composite of MO–GO and MO–RGO（M = Zn, Cd, Ni）. We sought to study the effect on the oxidation process through optical characterization via UV-Vis spectroscopy and Fourier Transform Infrared（FTIR） spectroscopy.Moreover, Thermo Gravimetric Analysis（TGA） was carried out to confirm 〉 90% weight loss in each process thus proving the reliability of the oxidation cycles. We have found that the nature of the oxidation process of graphite powder and its optical and electrochemical characteristics can be tuned by replacing the sodium nitrate（NaNO_3） by other metallic nitrates as Cd（NO_3）_2, Ni（NO_3）_2, and Zn（NO_3）_2. On the basis of obtained results, the synthesized GO and RGO may be expected as a promising material in antibacterial activity and in electrodes fabrication for energy devices such as solar cell, fuel cell,and super capacitors.

关键词： thermal properties of graphene oxide and reduced graphene oxide optical properties structuralproperties fuel cell composite materials

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Investigating Factors of Slope Failure for Different Landsliding Sites in Murree Area, Using Geomatics Techniques

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Journal of Geoscience and Environment Protection 2015年第8期3卷 39-45页

作者： Zia Ul mustafa Sajid Rashid Ahmad Muhammad Luqman usman Ahmad Samiullah Khan Muhammad Nawaz Asif Javed College of Earth and Environmental Sciences University of the Punjab Lahore Pakistan The Urban Unit Urban Sector Planning and Management Services Unit (Pvt.) Ltd. Lahore Pakistan Department of Space Science University of the Punjab Lahore Pakistan Punjab Group of Colleges Pattoki Campus Kasur Pakistan

Throughout the mountainous part of Pakistan, Murree is considered to host the worst slide affected areas. Landslide risk assessment, mapping and analysis is a labour intensive and time consuming work by using conventional field based methods. In this study Geomatics techniques have been applied on digital data such as satellite image and DEM, to investigate some possible causes of slope failure in selected landslide risk zones. The Remote sensing technology and GIS capabilities have been implemented using Landsat TM (30 m) multispectral data and Aster DEM (30 m). Satellite image and digital elevation model have been used to generate rock type map, aspect map, streams order map and slope map. The possible factors of slope failure for different zones of land sliding have been predicted by integrating information from all maps. It has been found that major causes of slope failure have been addressed, also it has been noted that water is the most dominant factor to cause land sliding in Murree area. Results are available for supporting hazard studies, disaster management and future development plans.

关键词： Landslide Pakistan Geomatics Hazard Landsat DEM GIS

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Quantification of Radiation Use Efficiency and Yield of Wheat as Influenced by Different Levels of Nitrogen and Water Stress under Semi-Arid Conditions of Faisalabad

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Agricultural Sciences 2018年第7期9卷 873-887页

作者： Muhammad Ishfaq usman Zulfiqar Muhammad Ahmad Ch Basit mustafa Ali Hamed Muhammad Shafique Aslam Muhammad Zohaib Anjum Department of Agronomy University of Agriculture Faisalabad Pakistan Department of Forestry and Range Management University of Agriculture Faisalabad Pakistan

Crop production is greatly influenced by water and nutrition stress in semi-arid areas. Nitrogen and water are two most important yield limiting factors which effect economic production of wheat. Drought initiates when large area of land suffers from absence of precipitation for temporary periods. Though, not only water scarceness but also low relative humidity and high temperature are other climate factors which induce drought condition. Whereas Effective nutrition (nitrogen) maintains crops metabolic activities and has the potential to lessen drought stress. According to study carried out to explore the influence of varying levels of potential soil moisture deficit (PSMD) and nitrogen, an experiment was planned at agronomy research area, University of Agriculture, Faisalabad. It was laid out in randomized complete block design (RCBD) with split plot arrangement, and replicated thrice. Two factors: potential soil moisture deficit levels (I1: irrigation at 50 mm PSMD, I2: irrigation at 75 mm PSMD and I3: irrigation at 100 mm PSMD) were randomized in main plots, while sub plot nitrogen levels {control (No nitrogen), 50, 100 and 150 kg N ha-1} were randomized. Adequate nitrogen application along with sufficient irrigation management gave highest yield. Under water deficit conditions adequate nitrogen application ameliorates the drought stress. Highest plant height (86.27 cm), number of productive tillers (320.0), grain·spike-1(49.73), test weight (50.55 g) and grain yield (6.72 t·ha-1) were observed with 75 mm PSMD and 150 kg·ha-1 application of nitrogen. While radiation use efficiency for dry matter accumulation of wheat ranged from 1.53 - 1.87 g·MJ-1 whereas, radiation use efficiency for grain yield ranged from 0.421 - 0.473 g·MJ-1. Results revealed that highest RUE obtained I3 (75 mm PSMD) and nitrogen application at 150 kg·ha-1. Judicial application of irrigation and fertilizer not only boosts the yield but also saves resource and increases former output.

关键词： Quantification Potential Soil Moisture Deficit Nitrogen Wheat

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印度尼西亚辣椒概况

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辣椒杂志 2010年第2期 46-49页

作者： usman mustafa Mubarik Ali Ir Heny Kuswanti 戴雄泽

印度尼西亚是世界上岛屿最多的国家,由Java、Sumatra、Sulawesi、Kalimantan和IrianJaya等5个较大的岛屿组成。辣椒是印度尼西亚人的重要蔬菜和调味佳品,咖喱饭调味品是最具特色的辣椒制品。辣椒在印度尼西亚多雨地区或灌溉条件较好的... 详细信息

印度尼西亚是世界上岛屿最多的国家,由Java、Sumatra、Sulawesi、Kalimantan和IrianJaya等5个较大的岛屿组成。辣椒是印度尼西亚人的重要蔬菜和调味佳品,咖喱饭调味品是最具特色的辣椒制品。辣椒在印度尼西亚多雨地区或灌溉条件较好的地区全年均可种植，主要种植基地集中在East Java、Central Java、West Java和North Sumatra等四个区域，West Java、East和Central Java的产量分别占全国总产量的23％、19％和12％。2003年，种植面积为17．6万hm^，生产鲜椒110万t，平均单产为6．1t／hm^2。

关键词：印度尼西亚辣椒制品 Central Java East 种植基地灌溉条件多雨地区

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泰国辣椒产业

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辣椒杂志 2010年第4期 46-49页

作者： usman mustafa Mubarik Ali Thongchai Satapornvorasak Orasa Dissataporn 戴雄泽

辣椒已成为泰国人饮食中主要和必须的消费品,人们喜欢辛辣味,辛辣食品在泰国快速发展,特辣食品很受欢迎且变得非常普遍。泰国不是辣椒原产地,一般认为在Ayutthaya Period时期由葡萄牙传教士在1511年以前传入泰国,

关键词：辣椒产业泰国辛辣食品消费品原产地传教士葡萄牙

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