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Showing 1 to 12 of 18 entries
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Physical and cognitive consequences of fatigue: A review.

Journal of advanced research

Abd-Elfattah HM, Abdelazeim FH, Elshennawy S.
PMID: 26257932
J Adv Res. 2015 May;6(3):351-8. doi: 10.1016/j.jare.2015.01.011. Epub 2015 Feb 24.

Fatigue is a common worrying complaint among people performing physical activities on the basis of training or rehabilitation. An enormous amount of research articles have been published on the topic of fatigue and its effect on physical and physiological...

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Abd-Elfattah HM, Abdelazeim FH, Elshennawy S. Physical and cognitive consequences of fatigue: A review. J Adv Res. 2015;6(3):351-8doi: 10.1016/j.jare.2015.01.011.
Abd-Elfattah, H. M., Abdelazeim, F. H., & Elshennawy, S. (2015). Physical and cognitive consequences of fatigue: A review. Journal of advanced research, 6(3), 351-8. https://doi.org/10.1016/j.jare.2015.01.011
Abd-Elfattah, Hoda M, et al. "Physical and cognitive consequences of fatigue: A review." Journal of advanced research vol. 6,3 (2015): 351-8. doi: https://doi.org/10.1016/j.jare.2015.01.011
Abd-Elfattah HM, Abdelazeim FH, Elshennawy S. Physical and cognitive consequences of fatigue: A review. J Adv Res. 2015 May;6(3):351-8. doi: 10.1016/j.jare.2015.01.011. Epub 2015 Feb 24. PMID: 26257932; PMCID: PMC4522584.
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Dysregulated MicroRNA Fingerprints and Methylation Patterns in Hepatocellular Carcinoma, Cancer Stem Cells, and Mesenchymal Stem Cells.

Frontiers in cell and developmental biology

Nasr MA, Salah RA, Abd Elkodous M, Elshenawy SE, El-Badri N.
PMID: 31681762
Front Cell Dev Biol. 2019 Oct 17;7:229. doi: 10.3389/fcell.2019.00229. eCollection 2019.

Hepatocellular carcinoma (HCC) is one of the top causes of cancer mortality worldwide. Although HCC has been researched extensively, there is still a need for novel and effective therapeutic interventions. There is substantial evidence that initiation of carcinogenesis in...

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Nasr MA, Salah RA, Abd Elkodous M, et al. Dysregulated MicroRNA Fingerprints and Methylation Patterns in Hepatocellular Carcinoma, Cancer Stem Cells, and Mesenchymal Stem Cells. Front Cell Dev Biol. 2019;7:229doi: 10.3389/fcell.2019.00229.
Nasr, M. A., Salah, R. A., Abd Elkodous, M., Elshenawy, S. E., & El-Badri, N. (2019). Dysregulated MicroRNA Fingerprints and Methylation Patterns in Hepatocellular Carcinoma, Cancer Stem Cells, and Mesenchymal Stem Cells. Frontiers in cell and developmental biology, 7229. https://doi.org/10.3389/fcell.2019.00229
Nasr, Mohamed A, et al. "Dysregulated MicroRNA Fingerprints and Methylation Patterns in Hepatocellular Carcinoma, Cancer Stem Cells, and Mesenchymal Stem Cells." Frontiers in cell and developmental biology vol. 7 (2019): 229. doi: https://doi.org/10.3389/fcell.2019.00229
Nasr MA, Salah RA, Abd Elkodous M, Elshenawy SE, El-Badri N. Dysregulated MicroRNA Fingerprints and Methylation Patterns in Hepatocellular Carcinoma, Cancer Stem Cells, and Mesenchymal Stem Cells. Front Cell Dev Biol. 2019 Oct 17;7:229. doi: 10.3389/fcell.2019.00229. eCollection 2019. PMID: 31681762; PMCID: PMC6811506.
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Behavioral, Cellular and Molecular Responses to Cold and Mechanical Stimuli in Rats with Bilateral Dopamine Depletion in the Mesencephalic Dopaminergic Neurons.

Neuroscience

Elshennawy M, Ouachikh O, Aissouni Y, Youssef S, Zaki SS, Durif F, Hafidi A.
PMID: 34748858
Neuroscience. 2021 Dec 15;479:107-124. doi: 10.1016/j.neuroscience.2021.10.026. Epub 2021 Nov 06.

Pain is the major non-motor symptom in Parkinson's disease (PD). Preclinical studies have mostly investigated mechanical pain by considering the decrease in a nociceptive threshold. Only a few studies have focused on thermal pain in animal models of PD....

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Elshennawy M, Ouachikh O, Aissouni Y, et al. Behavioral, Cellular and Molecular Responses to Cold and Mechanical Stimuli in Rats with Bilateral Dopamine Depletion in the Mesencephalic Dopaminergic Neurons. Neuroscience. 2021;479:107-124doi: 10.1016/j.neuroscience.2021.10.026.
Elshennawy, M., Ouachikh, O., Aissouni, Y., Youssef, S., Zaki, S. S., Durif, F., & Hafidi, A. (2021). Behavioral, Cellular and Molecular Responses to Cold and Mechanical Stimuli in Rats with Bilateral Dopamine Depletion in the Mesencephalic Dopaminergic Neurons. Neuroscience, 479107-124. https://doi.org/10.1016/j.neuroscience.2021.10.026
Elshennawy, Mennatallah, et al. "Behavioral, Cellular and Molecular Responses to Cold and Mechanical Stimuli in Rats with Bilateral Dopamine Depletion in the Mesencephalic Dopaminergic Neurons." Neuroscience vol. 479 (2021): 107-124. doi: https://doi.org/10.1016/j.neuroscience.2021.10.026
Elshennawy M, Ouachikh O, Aissouni Y, Youssef S, Zaki SS, Durif F, Hafidi A. Behavioral, Cellular and Molecular Responses to Cold and Mechanical Stimuli in Rats with Bilateral Dopamine Depletion in the Mesencephalic Dopaminergic Neurons. Neuroscience. 2021 Dec 15;479:107-124. doi: 10.1016/j.neuroscience.2021.10.026. Epub 2021 Nov 06. PMID: 34748858.
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Classification of Brain MRI Tumor Images Based on Deep Learning PGGAN Augmentation.

Diagnostics (Basel, Switzerland)

Gab Allah AM, Sarhan AM, Elshennawy NM.
PMID: 34943580
Diagnostics (Basel). 2021 Dec 13;11(12). doi: 10.3390/diagnostics11122343.

The wide prevalence of brain tumors in all age groups necessitates having the ability to make an early and accurate identification of the tumor type and thus select the most appropriate treatment plans. The application of convolutional neural networks...

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Gab Allah AM, Sarhan AM, Elshennawy NM. Classification of Brain MRI Tumor Images Based on Deep Learning PGGAN Augmentation. Diagnostics (Basel). 2021;11(12)doi: 10.3390/diagnostics11122343.
Gab Allah, A. M., Sarhan, A. M., & Elshennawy, N. M. (2021). Classification of Brain MRI Tumor Images Based on Deep Learning PGGAN Augmentation. Diagnostics (Basel, Switzerland), 11(12), . https://doi.org/10.3390/diagnostics11122343
Gab Allah, Ahmed M, et al. "Classification of Brain MRI Tumor Images Based on Deep Learning PGGAN Augmentation." Diagnostics (Basel, Switzerland) vol. 11,12 (2021). doi: https://doi.org/10.3390/diagnostics11122343
Gab Allah AM, Sarhan AM, Elshennawy NM. Classification of Brain MRI Tumor Images Based on Deep Learning PGGAN Augmentation. Diagnostics (Basel). 2021 Dec 13;11(12). doi: 10.3390/diagnostics11122343. PMID: 34943580.
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BCG vaccination and the risk of COVID 19: A possible correlation.

Virology

Ahmed SM, Nasr MA, Elshenawy SE, Hussein AE, El-Betar AH, Mohamed RH, El-Badri N.
PMID: 34742127
Virology. 2022 Jan 02;565:73-81. doi: 10.1016/j.virol.2021.10.003. Epub 2021 Oct 28.

Bacillus Calmette-Guérin (BCG) vaccine is currently used to prevent tuberculosis infection. The vaccine was found to enhance resistance to certain types of infection including positive sense RNA viruses. The current COVID-19 pandemic is caused by positive sense RNA, severe...

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Ahmed SM, Nasr MA, Elshenawy SE, et al. BCG vaccination and the risk of COVID 19: A possible correlation. Virology. 2021;565:73-81doi: 10.1016/j.virol.2021.10.003.
Ahmed, S. M., Nasr, M. A., Elshenawy, S. E., Hussein, A. E., El-Betar, A. H., Mohamed, R. H., & El-Badri, N. (2022). BCG vaccination and the risk of COVID 19: A possible correlation. Virology, 56573-81. https://doi.org/10.1016/j.virol.2021.10.003
Ahmed, Sara M, et al. "BCG vaccination and the risk of COVID 19: A possible correlation." Virology vol. 565 (2022): 73-81. doi: https://doi.org/10.1016/j.virol.2021.10.003
Ahmed SM, Nasr MA, Elshenawy SE, Hussein AE, El-Betar AH, Mohamed RH, El-Badri N. BCG vaccination and the risk of COVID 19: A possible correlation. Virology. 2022 Jan 02;565:73-81. doi: 10.1016/j.virol.2021.10.003. Epub 2021 Oct 28. PMID: 34742127; PMCID: PMC8552046.
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4.327 is the first impact factor for the Journal of Advanced Research; June 2018 - A success story!.

Journal of advanced research

Khaled HM, Elshennawy S.
PMID: 31193293
J Adv Res. 2019 Apr 19;17:1. doi: 10.1016/j.jare.2019.04.005. eCollection 2019 May.

No abstract available.

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Khaled HM, Elshennawy S. 4.327 is the first impact factor for the Journal of Advanced Research; June 2018 - A success story!. J Adv Res. 2019;17:1doi: 10.1016/j.jare.2019.04.005.
Khaled, H. M., & Elshennawy, S. (2019). 4.327 is the first impact factor for the Journal of Advanced Research; June 2018 - A success story!. Journal of advanced research, 171. https://doi.org/10.1016/j.jare.2019.04.005
Khaled, Hussein M, and Elshennawy, Shorouk. "4.327 is the first impact factor for the Journal of Advanced Research; June 2018 - A success story!." Journal of advanced research vol. 17 (2019): 1. doi: https://doi.org/10.1016/j.jare.2019.04.005
Khaled HM, Elshennawy S. 4.327 is the first impact factor for the Journal of Advanced Research; June 2018 - A success story!. J Adv Res. 2019 Apr 19;17:1. doi: 10.1016/j.jare.2019.04.005. eCollection 2019 May. PMID: 31193293; PMCID: PMC6526203.
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Utilizing deep learning models in CSI-based human activity recognition.

Neural computing & applications

Shalaby E, ElShennawy N, Sarhan A.
PMID: 35017796
Neural Comput Appl. 2022 Jan 07;1-18. doi: 10.1007/s00521-021-06787-w. Epub 2022 Jan 07.

In recent years, channel state information (CSI) in WiFi 802.11n has been increasingly used to collect data pertaining to human activity. Such raw data are then used to enhance human activity recognition. Activities such as lying down, falling, walking,...

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Shalaby E, ElShennawy N, Sarhan A. Utilizing deep learning models in CSI-based human activity recognition. Neural Comput Appl. 2022;1-18doi: 10.1007/s00521-021-06787-w.
Shalaby, E., ElShennawy, N., & Sarhan, A. (2022). Utilizing deep learning models in CSI-based human activity recognition. Neural computing & applications, 1-18. https://doi.org/10.1007/s00521-021-06787-w
Shalaby, Eman, et al. "Utilizing deep learning models in CSI-based human activity recognition." Neural computing & applications vol. (2022): 1-18. doi: https://doi.org/10.1007/s00521-021-06787-w
Shalaby E, ElShennawy N, Sarhan A. Utilizing deep learning models in CSI-based human activity recognition. Neural Comput Appl. 2022 Jan 07;1-18. doi: 10.1007/s00521-021-06787-w. Epub 2022 Jan 07. PMID: 35017796; PMCID: PMC8739002.
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Deep-Pneumonia Framework Using Deep Learning Models Based on Chest X-Ray Images.

Diagnostics (Basel, Switzerland)

Elshennawy NM, Ibrahim DM.
PMID: 32872384
Diagnostics (Basel). 2020 Aug 28;10(9). doi: 10.3390/diagnostics10090649.

Pneumonia is a contagious disease that causes ulcers of the lungs, and is one of the main reasons for death among children and the elderly in the world. Several deep learning models for detecting pneumonia from chest X-ray images...

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Elshennawy NM, Ibrahim DM. Deep-Pneumonia Framework Using Deep Learning Models Based on Chest X-Ray Images. Diagnostics (Basel). 2020;10(9)doi: 10.3390/diagnostics10090649.
Elshennawy, N. M., & Ibrahim, D. M. (2020). Deep-Pneumonia Framework Using Deep Learning Models Based on Chest X-Ray Images. Diagnostics (Basel, Switzerland), 10(9), . https://doi.org/10.3390/diagnostics10090649
Elshennawy, Nada M, and Ibrahim, Dina M. "Deep-Pneumonia Framework Using Deep Learning Models Based on Chest X-Ray Images." Diagnostics (Basel, Switzerland) vol. 10,9 (2020). doi: https://doi.org/10.3390/diagnostics10090649
Elshennawy NM, Ibrahim DM. Deep-Pneumonia Framework Using Deep Learning Models Based on Chest X-Ray Images. Diagnostics (Basel). 2020 Aug 28;10(9). doi: 10.3390/diagnostics10090649. PMID: 32872384; PMCID: PMC7554804.
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Hepatocellular carcinoma cell line-microenvironment induced cancer-associated phenotype, genotype and functionality in mesenchymal stem cells.

Life sciences

Salah RA, Nasr MA, El-Derby AM, Abd Elkodous M, Mohamed RH, El-Ekiaby N, Osama A, Elshenawy SE, Hamad MHM, Magdeldin S, Gabr MM, Abdelaziz AI, El-Badri NS.
PMID: 34826437
Life Sci. 2022 Jan 01;288:120168. doi: 10.1016/j.lfs.2021.120168. Epub 2021 Nov 23.

Mesenchymal stromal cells (MSCs) have shown promise in liver cancer treatment. However, when MSCs are recruited to hepatic site of injury, they acquire cancerous promoting phenotype.AIMS: To assess the influence of Hepatocellular carcinoma (HCC) microenvironment on human adipose MSCs...

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Salah RA, Nasr MA, El-Derby AM, et al. Hepatocellular carcinoma cell line-microenvironment induced cancer-associated phenotype, genotype and functionality in mesenchymal stem cells. Life Sci. 2021;288:120168doi: 10.1016/j.lfs.2021.120168.
Salah, R. A., Nasr, M. A., El-Derby, A. M., Abd Elkodous, M., Mohamed, R. H., El-Ekiaby, N., Osama, A., Elshenawy, S. E., Hamad, M. H. M., Magdeldin, S., Gabr, M. M., Abdelaziz, A. I., & El-Badri, N. S. (2022). Hepatocellular carcinoma cell line-microenvironment induced cancer-associated phenotype, genotype and functionality in mesenchymal stem cells. Life sciences, 288120168. https://doi.org/10.1016/j.lfs.2021.120168
Salah, Radwa Ayman, et al. "Hepatocellular carcinoma cell line-microenvironment induced cancer-associated phenotype, genotype and functionality in mesenchymal stem cells." Life sciences vol. 288 (2022): 120168. doi: https://doi.org/10.1016/j.lfs.2021.120168
Salah RA, Nasr MA, El-Derby AM, Abd Elkodous M, Mohamed RH, El-Ekiaby N, Osama A, Elshenawy SE, Hamad MHM, Magdeldin S, Gabr MM, Abdelaziz AI, El-Badri NS. Hepatocellular carcinoma cell line-microenvironment induced cancer-associated phenotype, genotype and functionality in mesenchymal stem cells. Life Sci. 2022 Jan 01;288:120168. doi: 10.1016/j.lfs.2021.120168. Epub 2021 Nov 23. PMID: 34826437.
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Utilizing deep learning models in CSI-based human activity recognition.

Neural computing & applications

Shalaby E, ElShennawy N, Sarhan A.
PMID: 35017796
Neural Comput Appl. 2022 Jan 07;1-18. doi: 10.1007/s00521-021-06787-w. Epub 2022 Jan 07.

In recent years, channel state information (CSI) in WiFi 802.11n has been increasingly used to collect data pertaining to human activity. Such raw data are then used to enhance human activity recognition. Activities such as lying down, falling, walking,...

Cite
Shalaby E, ElShennawy N, Sarhan A. Utilizing deep learning models in CSI-based human activity recognition. Neural Comput Appl. 2022;1-18doi: 10.1007/s00521-021-06787-w.
Shalaby, E., ElShennawy, N., & Sarhan, A. (2022). Utilizing deep learning models in CSI-based human activity recognition. Neural computing & applications, 1-18. https://doi.org/10.1007/s00521-021-06787-w
Shalaby, Eman, et al. "Utilizing deep learning models in CSI-based human activity recognition." Neural computing & applications vol. (2022): 1-18. doi: https://doi.org/10.1007/s00521-021-06787-w
Shalaby E, ElShennawy N, Sarhan A. Utilizing deep learning models in CSI-based human activity recognition. Neural Comput Appl. 2022 Jan 07;1-18. doi: 10.1007/s00521-021-06787-w. Epub 2022 Jan 07. PMID: 35017796; PMCID: PMC8739002.
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One Anastomosis Gastric Bypass Versus Long Biliopancreatic Limb Roux-en-Y Gastric Bypass.

Obesity surgery

Ibrahim MY, Elshennawy AS, Wassef ATS, Salah A, Hassan AM, Mikhail S.
PMID: 35013896
Obes Surg. 2022 Jan 11; doi: 10.1007/s11695-021-05874-0. Epub 2022 Jan 11.

BACKGROUND: Roux-en-Y gastric bypass (RYGB) is one of the most effective bariatric procedures. The study aimed to explore the value of lengthening the biliopancreatic limb (BPL) in RYGB compared to the outcome of one-anastomosis gastric bypass (OAGB).METHODS: This prospective...

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Ibrahim MY, Elshennawy AS, Wassef ATS, et al. One Anastomosis Gastric Bypass Versus Long Biliopancreatic Limb Roux-en-Y Gastric Bypass. Obes Surg. 2022;doi: 10.1007/s11695-021-05874-0.
Ibrahim, M. Y., Elshennawy, A. S., Wassef, A. T. S., Salah, A., Hassan, A. M., & Mikhail, S. (2022). One Anastomosis Gastric Bypass Versus Long Biliopancreatic Limb Roux-en-Y Gastric Bypass. Obesity surgery, . https://doi.org/10.1007/s11695-021-05874-0
Ibrahim, Mohamed Y, et al. "One Anastomosis Gastric Bypass Versus Long Biliopancreatic Limb Roux-en-Y Gastric Bypass." Obesity surgery vol. (2022). doi: https://doi.org/10.1007/s11695-021-05874-0
Ibrahim MY, Elshennawy AS, Wassef ATS, Salah A, Hassan AM, Mikhail S. One Anastomosis Gastric Bypass Versus Long Biliopancreatic Limb Roux-en-Y Gastric Bypass. Obes Surg. 2022 Jan 11; doi: 10.1007/s11695-021-05874-0. Epub 2022 Jan 11. PMID: 35013896.
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Classification of Brain MRI Tumor Images Based on Deep Learning PGGAN Augmentation.

Diagnostics (Basel, Switzerland)

Gab Allah AM, Sarhan AM, Elshennawy NM.
PMID: 34943580
Diagnostics (Basel). 2021 Dec 13;11(12). doi: 10.3390/diagnostics11122343.

The wide prevalence of brain tumors in all age groups necessitates having the ability to make an early and accurate identification of the tumor type and thus select the most appropriate treatment plans. The application of convolutional neural networks...

Cite
Gab Allah AM, Sarhan AM, Elshennawy NM. Classification of Brain MRI Tumor Images Based on Deep Learning PGGAN Augmentation. Diagnostics (Basel). 2021;11(12)doi: 10.3390/diagnostics11122343.
Gab Allah, A. M., Sarhan, A. M., & Elshennawy, N. M. (2021). Classification of Brain MRI Tumor Images Based on Deep Learning PGGAN Augmentation. Diagnostics (Basel, Switzerland), 11(12), . https://doi.org/10.3390/diagnostics11122343
Gab Allah, Ahmed M, et al. "Classification of Brain MRI Tumor Images Based on Deep Learning PGGAN Augmentation." Diagnostics (Basel, Switzerland) vol. 11,12 (2021). doi: https://doi.org/10.3390/diagnostics11122343
Gab Allah AM, Sarhan AM, Elshennawy NM. Classification of Brain MRI Tumor Images Based on Deep Learning PGGAN Augmentation. Diagnostics (Basel). 2021 Dec 13;11(12). doi: 10.3390/diagnostics11122343. PMID: 34943580.
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Showing 1 to 12 of 18 entries