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Article ; Online: NCAM protein and SARS-COV-2 surface proteins: In-silico hypothetical evidence for the immunopathogenesis of Guillain-Barré syndrome.

Morsy, Sara

2020 Volume 145, Page(s) 110342

Abstract: This study aimed at identifying human neural proteins that can be attacked by cross-reacting SARS ... from literature. These human proteins were compared to SARS-COV-2 surface proteins to identify ... for further analysis. Similar human and SARS-COV-2 epitopes were docked to the corresponding MHC molecule ...

Abstract	This study aimed at identifying human neural proteins that can be attacked by cross-reacting SARS-COV-2 antibodies causing Guillain-Barré syndrome. These markers can be used for the diagnosis of Guillain-Barré syndrome (GBS). To achieve this goal, proteins implicated in the development of GBS were retrieved from literature. These human proteins were compared to SARS-COV-2 surface proteins to identify homologous sequences using Blastp. Then, MHC-I and MHC-II epitopes were determined in the homologous sequences and used for further analysis. Similar human and SARS-COV-2 epitopes were docked to the corresponding MHC molecule to compare the binding pattern of human and SARS-COV-2 proteins to the MHC molecule. Neural cell adhesion molecule is the only neural protein that showed homologous sequence to SARS-COV-2 envelope protein. The homologous sequence was part of HLA-A68 and HLA-DQA/HLA-DQB epitopes had a similar binding pattern to SARS-COV-2 envelope protein. Based on these results, the study suggests that NCAM may play a significant role in the immunopathogenesis of GBS. NCAM antibodies can be used as a marker for Guillain-Barré syndrome. However, more experimental studies are needed to prove these results.
MeSH term(s)	Amino Acid Motifs ; CD56 Antigen/chemistry ; COVID-19/immunology ; Computational Biology ; Computer Simulation ; Coronavirus Envelope Proteins/chemistry ; Crystallography, X-Ray ; Epitopes/chemistry ; Guillain-Barre Syndrome/immunology ; HLA-A Antigens/chemistry ; HLA-DQ alpha-Chains/chemistry ; HLA-DQ beta-Chains/chemistry ; Humans ; Major Histocompatibility Complex ; Models, Theoretical ; Peptides/chemistry ; Protein Binding ; SARS-CoV-2 ; Viral Proteins/chemistry
Chemical Substances	CD56 Antigen ; Coronavirus Envelope Proteins ; Epitopes ; HLA-A Antigens ; HLA-A*68 antigen ; HLA-DQ alpha-Chains ; HLA-DQ beta-Chains ; HLA-DQA1 antigen ; HLA-DQbeta antigen ; NCAM1 protein, human ; Peptides ; Viral Proteins ; envelope protein, SARS-CoV-2
Keywords	covid19
Language	English
Publishing date	2020-10-08
Publishing country	United States
Document type	Journal Article
ZDB-ID	193145-3
ISSN	1532-2777 ; 0306-9877
ISSN (online)	1532-2777
ISSN	0306-9877
DOI	10.1016/j.mehy.2020.110342
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Article ; Online: Epitope mimicry analysis of SARS-COV-2 surface proteins and human lung proteins.

Morsy, Sara / Morsy, Ahmed

Journal of molecular graphics & modelling

2021 Volume 105, Page(s) 107836

Abstract: Background: Autoimmune response after the infection of SARS-COV-2 is evident as more cases ... of autoimmune lung injury.: Methods: We extracted the peptide sequences of surface proteins of the SARS-COV-2 ... that had a similar binding pattern to SARS-COV-2 as human proteins were HLA-A and HLA-DP.: Conclusion ...

Abstract	Background: Autoimmune response after the infection of SARS-COV-2 is evident as more cases of Guillain Barre syndrome and Kawasaki disease are diagnosed. In this study, we aim to investigate a possible mechanism of autoimmune lung injury. Methods: We extracted the peptide sequences of surface proteins of the SARS-COV-2 from the NCBI data protein. We used Blastp to assess the homologous sequences between the human proteins in the UNIPROT database that are associated with respiratory distress. Then, we filtered the homologous sequences to those selectively expressed in the lung and homologous to surface viral proteins. We then assessed the epitope sequences for MHC-I and MHC-II using recommended settings and reference MHC in the IEDB database. Results: Homeobox protein 2.1 (NKX2-1) and ATP-binding cassette sub-family A member 3 (ABCA3) showed homologous sequence to both surface glycoproteins and envelope proteins. The HLA-DR and HLA-DQ had a similar binding pattern to ABCA3 as surface glycoproteins and envelope proteins, respectively. Other HLA molecules that had a similar binding pattern to SARS-COV-2 as human proteins were HLA-A and HLA-DP. Conclusion: Our study indicates that there is a possible autoimmune mechanism underlying the acute respiratory distress syndrome in SARS-COV-2.
MeSH term(s)	COVID-19 ; Epitopes ; Humans ; Lung ; Membrane Proteins ; SARS-CoV-2
Chemical Substances	Epitopes ; Membrane Proteins
Language	English
Publishing date	2021-02-04
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1396450-1
ISSN	1873-4243 ; 1093-3263
ISSN (online)	1873-4243
ISSN	1093-3263
DOI	10.1016/j.jmgm.2021.107836
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Article: NCAM protein and SARS-COV-2 surface proteins: In-silico hypothetical evidence for the immunopathogenesis of Guillain-Barré syndrome

Morsy, Sara

Med Hypotheses

Abstract	This study aimed at identifying human neural proteins that can be attacked by cross-reacting SARS-COV-2 antibodies causing Guillain-Barré syndrome. These markers can be used for the diagnosis of Guillain-Barré syndrome (GBS). To achieve this goal, proteins implicated in the development of GBS were retrieved from literature. These human proteins were compared to SARS-COV-2 surface proteins to identify homologous sequences using Blastp. Then, MHC-I and MHC-II epitopes were determined in the homologous sequences and used for further analysis. Similar human and SARS-COV-2 epitopes were docked to the corresponding MHC molecule to compare the binding pattern of human and SARS-COV-2 proteins to the MHC molecule. Neural cell adhesion molecule is the only neural protein that showed homologous sequence to SARS-COV-2 envelope protein. The homologous sequence was part of HLA-A68 and HLA-DQA/HLA-DQB epitopes had a similar binding pattern to SARS-COV-2 envelope protein. Based on these results, the study suggests that NCAM may play a significant role in the immunopathogenesis of GBS. NCAM antibodies can be used as a marker for Guillain-Barré syndrome. However, more experimental studies are needed to prove these results.
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #838161
Database	COVID19

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Article ; Online: Anticancer evaluations of iodoquinazoline substituted with allyl and/or benzyl as dual inhibitors of EGFR

Aljohani, Ahmed K B / El-Adl, Khaled / Almohaywi, Basmah / Alatawi, Omar M / Alsulaimany, Marwa / El-Morsy, Ahmed / Almadani, Sara A / Alharbi, Hussam Y / Aljohani, Majed S / Abdulhaleem M, Felemban Athary / Osman, Hanan E M / Mohamady, Samy

RSC advances

2024 Volume 14, Issue 12, Page(s) 7964–7980

Abstract: Fifteen new iodoquinazoline derivatives, 5a,b to 18, are reported in this study and their anticancer evaluation as dual inhibitors of ... ...

Abstract	Fifteen new iodoquinazoline derivatives, 5a,b to 18, are reported in this study and their anticancer evaluation as dual inhibitors of EGFR
Language	English
Publishing date	2024-03-06
Publishing country	England
Document type	Journal Article
ISSN	2046-2069
ISSN (online)	2046-2069
DOI	10.1039/d4ra00502c
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Does local vaginal estrogen after tension-free transobturator vaginal tape reduce overactive bladder symptoms in postmenopausal women? A prospective randomized, controlled study.

Morsy, Samer Mahmoud / Farouk, Dalia / Hassan, Sara / Abdelaziz, Ahmed Yehia / Hussein, Hussein Aly

Asian journal of urology

2022 Volume 11, Issue 1, Page(s) 86–92

Abstract: Objective: We aimed to evaluate the efficacy of topical estrogen after transvaginal tension-free vaginal tape-obturator (TVT-O) in the treatment of : Methods: This is a prospective randomized controlled study performed in the Urology and Gynecology ... ...

Abstract	Objective: We aimed to evaluate the efficacy of topical estrogen after transvaginal tension-free vaginal tape-obturator (TVT-O) in the treatment of Methods: This is a prospective randomized controlled study performed in the Urology and Gynecology Departments, Kasr Al Ainy Hospital, Cairo University, Cairo, Egypt. Two hundred and ten postmenopausal females presenting during the period between January 2017 and November 2020 with stress urinary incontinence were included in the study. Patients were divided into two groups, 105 patients in Group A (treatment group) and 105 patients in Group B (control group). Patients in Group A underwent transvaginal TVT-O followed by local vaginal estrogen treatment for 6 months, while patients in Group B underwent transvaginal TVT-O only. The study included any postmenopausal female with urodynamic stress urinary incontinence. All patients had to fulfill a 3-day bladder diary, overactive bladder symptoms score, urine analysis, urodynamic study, and post-voiding residual urine measurement by abdominal ultrasound preoperatively and at 3-month and 6-month follow-ups. Results: At 6-month follow-up, daytime frequency was reduced to 8% in Group A (increased to 21% in Group B) with a statistically significant difference between both groups ( Conclusion: Local vaginal estrogen treatment given to postmenopausal patients after midurethral sling procedures can reduce the symptoms of daytime frequency and urinary urgency. Long-term follow-up is needed.
Language	English
Publishing date	2022-11-03
Publishing country	Singapore
Document type	Journal Article
ZDB-ID	2831144-9
ISSN	2214-3882
ISSN	2214-3882
DOI	10.1016/j.ajur.2022.03.014
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Book ; Online: Context-aware Non-linear and Neural Attentive Knowledge-based Models for Grade Prediction

Morsy, Sara / Karypis, George

2020

Abstract: Grade prediction for future courses not yet taken by students is important as it can help them and their advisers during the process of course selection as well as for designing personalized degree plans and modifying them based on their performance. One ...

Abstract	Grade prediction for future courses not yet taken by students is important as it can help them and their advisers during the process of course selection as well as for designing personalized degree plans and modifying them based on their performance. One of the successful approaches for accurately predicting a student's grades in future courses is Cumulative Knowledge-based Regression Models (CKRM). CKRM learns shallow linear models that predict a student's grades as the similarity between his/her knowledge state and the target course. However, prior courses taken by a student can have \black{different contributions when estimating a student's knowledge state and towards each target course, which} cannot be captured by linear models. Moreover, CKRM and other grade prediction methods ignore the effect of concurrently-taken courses on a student's performance in a target course. In this paper, we propose context-aware non-linear and neural attentive models that can potentially better estimate a student's knowledge state from his/her prior course information, as well as model the interactions between a target course and concurrent courses. Compared to the competing methods, our experiments on a large real-world dataset consisting of more than $1.5$M grades show the effectiveness of the proposed models in accurately predicting students' grades. Moreover, the attention weights learned by the neural attentive model can be helpful in better designing their degree plans. Comment: arXiv admin note: substantial text overlap with arXiv:1904.11858
Keywords	Computer Science - Machine Learning ; Computer Science - Computers and Society ; Statistics - Machine Learning
Subject code	370 ; 006
Publishing date	2020-03-09
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Synthesis of New Monoazo Disperse Dyes for Dyeing Polyester Fabric Using Two Different Dyeing Methods: Demonstration of Their Antibacterial and Anticancer Activities.

Abdelmoteleb, Khaled M A / El-Apasery, Morsy A / Wasfy, Ashraf A F / Ahmed, Sara M

Polymers

2023 Volume 15, Issue 14

Abstract: 3-(dimethylamino)-1-phenylprop-2-en-1-ones were obtained with good yields by reacting dimethylformamide dimethylacetal with different methyl ketones. 3-oxo-3-phenyl-2-(2-phenylhydrazono)propanals disperse dyes were obtained via reacting of 3-( ... ...

Abstract	3-(dimethylamino)-1-phenylprop-2-en-1-ones were obtained with good yields by reacting dimethylformamide dimethylacetal with different methyl ketones. 3-oxo-3-phenyl-2-(2-phenylhydrazono)propanals disperse dyes were obtained via reacting of 3-(dimethylamino)-1-phenylprop-2-en-1-ones with phenyldiazonium chloride. The novel dyes were used in dyeing polyester fabrics through two different dyeing methods at temperatures of 100 and 130 °C. We found that the color strength when using the dyeing method at 130 °C was better than the dyeing method at 100 °C. The fastness properties of dyed fabrics with these new disperse dyes were studied and gave very good results (except for fastness to light, which gave moderate results). The new dyes were evaluated against some different types of bacteria and cancer, which showed excellent and promising results for the possibility of using these dyes as antibacterial and anticancer agents.
Language	English
Publishing date	2023-07-15
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527146-5
ISSN	2073-4360 ; 2073-4360
ISSN (online)	2073-4360
ISSN	2073-4360
DOI	10.3390/polym15143052
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Sparse Neural Attentive Knowledge-based Models for Grade Prediction

Morsy, Sara / Karypis, George

2019

Abstract	Grade prediction for future courses not yet taken by students is important as it can help them and their advisers during the process of course selection as well as for designing personalized degree plans and modifying them based on their performance. One of the successful approaches for accurately predicting a student's grades in future courses is Cumulative Knowledge-based Regression Models (CKRM). CKRM learns shallow linear models that predict a student's grades as the similarity between his/her knowledge state and the target course. A student's knowledge state is built by linearly accumulating the learned provided knowledge components of the courses he/she has taken in the past, weighted by his/her grades in them. However, not all the prior courses contribute equally to the target course. In this paper, we propose a novel Neural Attentive Knowledge-based model (NAK) that learns the importance of each historical course in predicting the grade of a target course. Compared to CKRM and other competing approaches, our experiments on a large real-world dataset consisting of $\sim$1.5 grades show the effectiveness of the proposed NAK model in accurately predicting the students' grades. Moreover, the attention weights learned by the model can be helpful in better designing their degree plans. Comment: accepted for publication in EDM 2019
Keywords	Computer Science - Computers and Society ; Computer Science - Machine Learning ; Statistics - Machine Learning
Subject code	370
Publishing date	2019-04-22
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Will this Course Increase or Decrease Your GPA? Towards Grade-aware Course Recommendation

Morsy, Sara / Karypis, George

2019

Abstract: In order to help undergraduate students towards successfully completing their degrees, developing tools that can assist students during the course selection process is a significant task in the education domain. The optimal set of courses for each ... ...

Abstract	In order to help undergraduate students towards successfully completing their degrees, developing tools that can assist students during the course selection process is a significant task in the education domain. The optimal set of courses for each student should include courses that help him/her graduate in a timely fashion and for which he/she is well-prepared for so as to get a good grade in. To this end, we propose two different grade-aware course recommendation approaches to recommend to each student his/her optimal set of courses. The first approach ranks the courses by using an objective function that differentiates between courses that are expected to increase or decrease a student's GPA. The second approach combines the grades predicted by grade prediction methods with the rankings produced by course recommendation methods to improve the final course rankings. To obtain the course rankings in the first approach, we adapt two widely-used representation learning techniques to learn the optimal temporal ordering between courses. Our experiments on a large dataset obtained from the University of Minnesota that includes students from 23 different majors show that the grade-aware course recommendation methods can do better on recommending more courses in which the students are expected to perform well and recommending fewer courses in which they are expected not to perform well in than grade-unaware course recommendation methods. Comment: Under revision for Journal of Educational Data Mining (JEDM)
Keywords	Computer Science - Information Retrieval ; Computer Science - Machine Learning ; Statistics - Machine Learning
Subject code	370
Publishing date	2019-04-22
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Quinazolines and thiazolidine-2,4-dions as SARS-CoV-2 inhibitors: repurposing,

El-Hddad, Sanadelaslam S A / Sobhy, Mohamed H / El-Morsy, Ahmed / Shoman, Nabil A / El-Adl, Khaled

RSC advances

2024 Volume 14, Issue 19, Page(s) 13237–13250

Abstract: This paper presents an extensive analysis of COVID-19 with a specific focus on VEGFR-2 inhibitors as potential treatments. The investigation includes an overview of computational methodologies employed in drug repurposing and ... ...

Abstract	This paper presents an extensive analysis of COVID-19 with a specific focus on VEGFR-2 inhibitors as potential treatments. The investigation includes an overview of computational methodologies employed in drug repurposing and highlights
Language	English
Publishing date	2024-04-23
Publishing country	England
Document type	Journal Article
ISSN	2046-2069
ISSN (online)	2046-2069
DOI	10.1039/d4ra02029d
Database	MEDical Literature Analysis and Retrieval System OnLINE

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