Amer Sohail Kashif

Dr. Amer Sohail Kashif


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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13 March 2020 in Sensors
Verified
Journal Article
Open access
PDF file
KZKashan Zafar
Kashan Zafar
SGSyed Gilani
Syed Gilani
AWAsim Waris
Asim Waris
Ali AhmedAli Ahmed
Ali Ahmed
Mohsin JamilMohsin Jamil
Mohsin Jamil
AKAmer Sohail Kashif
Amer Sohail Kashif
Clinical treatment of skin lesion is primarily dependent on timely detection and delimitation of lesion boundaries for accurate cancerous region localization. Prevalence of skin cancer is on the higher side, especially that of melanoma, which is aggressive in nature due to its high metastasis rate. Therefore, timely diagnosis is critical for its treatment before the onset of malignancy. To address this problem, medical imaging is used for the analysis and segmentation of lesion boundaries from dermoscopic images. Various methods have been used, ranging from visual inspection to the textural analysis of the images. However, accuracy of these methods is low for proper clinical treatment because of the sensitivity involved in surgical procedures or drug application. This presents an opportunity to develop an automated model with good accuracy so that it may be used in a clinical setting. This paper proposes an automated method for segmenting lesion boundaries that combines two architectures, the U-Net and the ResNet, collectively called Res-Unet. Moreover, we also used image inpainting for hair removal, which improved the segmentation results significantly. We trained our model on the ISIC 2017 dataset and validated it on the ISIC 2017 test set as well as the PH2 dataset. Our proposed model attained a Jaccard Index of 0.772 on the ISIC 2017 test set and 0.854 on the PH2 dataset, which are comparable results to the current available state-of-the-art techniques.

3 February 2023 in Molecules
Verified
Journal Article
Open access
PDF file
TMTuba Maryam
Tuba Maryam
NRNosheen Fatima Rana
Nosheen Fatima Rana
SASultan Alshahrani
Sultan Alshahrani
FBFarhat Batool
Farhat Batool
MFMisha Fatima
Misha Fatima
Farid MenaaFarid Menaa
Farid Menaa
Wilson’s disease causes copper accumulation in the liver and extrahepatic organs. The available therapies aim to lower copper levels by various means. However, a potent drug that can repair the damaged liver and brain tissue is needed. Silymarin has hepatoprotective, antioxidant, and cytoprotective properties. However, poor oral bioavailability reduces its efficacy. In this study, a “thin film hydration method” was used for synthesizing silymarin-encapsulated liposome nanoparticles (SLNPs) and evaluated them against copper toxicity, associated liver dysfunction and neurobehavioral abnormalities in Wistar rats. After copper toxicity induction, serological and behavioral assays were conducted to evaluate treatment approaches. Histological examination of the diseased rats revealed severe hepatocyte necrosis and neuronal vacuolation. These cellular degenerations were mild in rats treated with SLNPs and a combination of zinc and SLNPs (ZSLNPs). SLNPs also decreased liver enzymes and enhanced rats’ spatial memory significantly (p = 0.006) in the diseased rats. During forced swim tests, SLNPs treated rats exhibited a 60-s reduction in the immobility period, indicating reduced depression. ZSLNPs were significantly more effective than traditional zinc therapy in decreasing the immobility period (p = 0.0008) and reducing liver enzymes, but not in improving spatial memory. Overall, SLNPs enhanced oral silymarin administration and managed copper toxicity symptoms.

2 August 2022 in Polymers
Verified
Journal Article
Open access
PDF file
SAShabia Azhar
Shabia Azhar
NRNosheen Fatima Rana
Nosheen Fatima Rana
AKAmer Sohail Kashif
Amer Sohail Kashif
TTTahreem Tanweer
Tahreem Tanweer
ISIqra Shafique
Iqra Shafique
Farid MenaaFarid Menaa
Farid Menaa
Micro-crack formation and resultant bacterial infiltration are major causes of secondary caries formation in dental resin-based composite restorations. Improving dental resin composites’ mechanical and biological properties using highly bendable nanoparticles (NPs) can resolve this issue. This study aims to develop novel Diethylaminoethyl (DEAE)-Dextran silver nanoparticles (AgNPs) and subsequently modify composite resins with these NPs to enhance their mechanical and antibacterial properties. DEAE-Dextran AgNPs were successfully synthesized using a chemical reduction method that was confirmed with the help of ultraviolet-visible (UV-Vis) spectroscopy, scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), Zeta potential, and energy-dispersive X-ray spectroscopy (EDS). Antibacterial activity of a composite disc with DEAE-Dextran AgNPs was tested against Streptococcus mutans, Enterococcus faecalis, and oral microcosm. The composite discs prepared with DEAE-Dextran AgNPs exhibited excellent antibacterial activity compared with composite resin reinforced by simple AgNPs (p < 0.05). Mechanical properties were significantly enhanced by adding DEAE-Dextran into composite resin (p < 0.05). Moreover, unlike AgNPs, DEAE-Dextran AgNPs were found to be less hemolytic. The results establish strong ground applications for DEAE-Dextran-modified dental composite resins in restorative dental applications.
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24 February 2021 in Sensors
Verified
Journal Article
Open access
PDF file
AFAQ NOORAFAQ NOOR
AFAQ NOOR
AWAsim Waris
Asim Waris
SGSyed Gilani
Syed Gilani
AKAmer Sohail Kashif
Amer Sohail Kashif
MJMads Jochumsen
Mads Jochumsen
Imran Khan NiaziImran Khan Niazi
Imran Khan Niazi
Stroke is a cerebrovascular disease (CVD), which results in hemiplegia, paralysis, or death. Conventionally, a stroke patient requires prolonged sessions with physical therapists for the recovery of motor function. Various home-based rehabilitative devices are also available for upper limbs and require minimal or no assistance from a physiotherapist. However, there is no clinically proven device available for functional recovery of a lower limb. In this study, we explored the potential use of surface electromyography (sEMG) as a controlling mechanism for the development of a home-based lower limb rehabilitative device for stroke patients. In this experiment, three channels of sEMG were used to record data from 11 stroke patients while performing ankle joint movements. The movements were then decoded from the sEMG data and their correlation with the level of motor impairment was investigated. The impairment level was quantified using the Fugl-Meyer Assessment (FMA) scale. During the analysis, Hudgins time-domain features were extracted and classified using linear discriminant analysis (LDA) and artificial neural network (ANN). On average, 63.86% ± 4.3% and 67.1% ± 7.9% of the movements were accurately classified in an offline analysis by LDA and ANN, respectively. We found that in both classifiers, some motions outperformed others (p < 0.001 for LDA and p = 0.014 for ANN). The Spearman correlation (ρ) was calculated between the FMA scores and classification accuracies. The results indicate that there is a moderately positive correlation (ρ = 0.75 for LDA and ρ = 0.55 for ANN) between the two of them. The findings of this study suggest that a home-based EMG system can be developed to provide customized therapy for the improvement of functional lower limb motion in stroke patients.