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Removing a Cystein Group On Interferon Alpha 2b at Position 2 and 99 does Not Diminish Antitumor Activity of the Protein, Even Better.

Scientia pharmaceutica

Rachmawati H, Jessica A, Sumirtaputra YC, Retnoningrum DS, Adlia A, Ningrum RA.
PMID: 27110503
Sci Pharm. 2016 Feb 14;84(1):113-30. doi: 10.3797/scipharm.ISP.2015.04. Print 2016.

Interferon alpha 2b is the only standard therapeutic protein for hepatitis virus infections. Further study demonstrated that this protein also posseses antitumor activity in several cancerous organs. One main pathway of this antitumor activity is mediated through antiproliferation as...

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Rachmawati H, Jessica A, Sumirtaputra YC, et al. Removing a Cystein Group On Interferon Alpha 2b at Position 2 and 99 does Not Diminish Antitumor Activity of the Protein, Even Better. Sci Pharm. 2016;84(1):113-30doi: 10.3797/scipharm.ISP.2015.04.
Rachmawati, H., Jessica, A., Sumirtaputra, Y. C., Retnoningrum, D. S., Adlia, A., & Ningrum, R. A. (2016). Removing a Cystein Group On Interferon Alpha 2b at Position 2 and 99 does Not Diminish Antitumor Activity of the Protein, Even Better. Scientia pharmaceutica, 84(1), 113-30. https://doi.org/10.3797/scipharm.ISP.2015.04
Rachmawati, Heni, et al. "Removing a Cystein Group On Interferon Alpha 2b at Position 2 and 99 does Not Diminish Antitumor Activity of the Protein, Even Better." Scientia pharmaceutica vol. 84,1 (2016): 113-30. doi: https://doi.org/10.3797/scipharm.ISP.2015.04
Rachmawati H, Jessica A, Sumirtaputra YC, Retnoningrum DS, Adlia A, Ningrum RA. Removing a Cystein Group On Interferon Alpha 2b at Position 2 and 99 does Not Diminish Antitumor Activity of the Protein, Even Better. Sci Pharm. 2016 Feb 14;84(1):113-30. doi: 10.3797/scipharm.ISP.2015.04. Print 2016. PMID: 27110503; PMCID: PMC4839551.
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Patient-factors associated with metformin steady-state levels in type 2 diabetes mellitus with therapeutic dosage.

Journal of clinical & translational endocrinology

Ningrum VDA, Ikawati Z, Sadewa AH, Ikhsan MR.
PMID: 29892566
J Clin Transl Endocrinol. 2018 May 13;12:42-47. doi: 10.1016/j.jcte.2018.05.001. eCollection 2018 Jun.

AIMS: This prospective study aimed to analyze metformin steady-state concentration in repeated constant dosage and the influencing patient-factors as well as to correlate them with glycemic control.METHODS: The validated HPLC-UV method was used to examine metformin steady-state concentration, while...

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Ningrum VDA, Ikawati Z, Sadewa AH, et al. Patient-factors associated with metformin steady-state levels in type 2 diabetes mellitus with therapeutic dosage. J Clin Transl Endocrinol. 2018;12:42-47doi: 10.1016/j.jcte.2018.05.001.
Ningrum, V. D. A., Ikawati, Z., Sadewa, A. H., & Ikhsan, M. R. (2018). Patient-factors associated with metformin steady-state levels in type 2 diabetes mellitus with therapeutic dosage. Journal of clinical & translational endocrinology, 1242-47. https://doi.org/10.1016/j.jcte.2018.05.001
Ningrum, Vitarani D A, et al. "Patient-factors associated with metformin steady-state levels in type 2 diabetes mellitus with therapeutic dosage." Journal of clinical & translational endocrinology vol. 12 (2018): 42-47. doi: https://doi.org/10.1016/j.jcte.2018.05.001
Ningrum VDA, Ikawati Z, Sadewa AH, Ikhsan MR. Patient-factors associated with metformin steady-state levels in type 2 diabetes mellitus with therapeutic dosage. J Clin Transl Endocrinol. 2018 May 13;12:42-47. doi: 10.1016/j.jcte.2018.05.001. eCollection 2018 Jun. PMID: 29892566; PMCID: PMC5992324.
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Application of cell culture technology and genetic engineering for production of future foods and crop improvement to strengthen food security.

Bioengineered

Wikandari R, Manikharda, Baldermann S, Ningrum A, Taherzadeh MJ.
PMID: 34779353
Bioengineered. 2021 Dec;12(2):11305-11330. doi: 10.1080/21655979.2021.2003665.

The growing population and the climate changes put a pressure on food production globally, therefore a fundamental transformation of food production is required. One approach to accelerate food production is application of modern biotechnology such as cell culture, marker...

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Wikandari R, Manikharda, Baldermann S, et al. Application of cell culture technology and genetic engineering for production of future foods and crop improvement to strengthen food security. Bioengineered. 2021;12(2):11305-11330doi: 10.1080/21655979.2021.2003665.
Wikandari, R., Manikharda, Baldermann, S., Ningrum, A., & Taherzadeh, M. J. (2021). Application of cell culture technology and genetic engineering for production of future foods and crop improvement to strengthen food security. Bioengineered, 12(2), 11305-11330. https://doi.org/10.1080/21655979.2021.2003665
Wikandari, Rachma, et al. "Application of cell culture technology and genetic engineering for production of future foods and crop improvement to strengthen food security." Bioengineered vol. 12,2 (2021): 11305-11330. doi: https://doi.org/10.1080/21655979.2021.2003665
Wikandari R, Manikharda, Baldermann S, Ningrum A, Taherzadeh MJ. Application of cell culture technology and genetic engineering for production of future foods and crop improvement to strengthen food security. Bioengineered. 2021 Dec;12(2):11305-11330. doi: 10.1080/21655979.2021.2003665. PMID: 34779353.
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Application of cell culture technology and genetic engineering for production of future foods and crop improvement to strengthen food security.

Bioengineered

Wikandari R, Manikharda, Baldermann S, Ningrum A, Taherzadeh MJ.
PMID: 34779353
Bioengineered. 2021 Dec;12(2):11305-11330. doi: 10.1080/21655979.2021.2003665.

The growing population and the climate changes put a pressure on food production globally, therefore a fundamental transformation of food production is required. One approach to accelerate food production is application of modern biotechnology such as cell culture, marker...

Cite
Wikandari R, Manikharda, Baldermann S, et al. Application of cell culture technology and genetic engineering for production of future foods and crop improvement to strengthen food security. Bioengineered. 2021;12(2):11305-11330doi: 10.1080/21655979.2021.2003665.
Wikandari, R., Manikharda, Baldermann, S., Ningrum, A., & Taherzadeh, M. J. (2021). Application of cell culture technology and genetic engineering for production of future foods and crop improvement to strengthen food security. Bioengineered, 12(2), 11305-11330. https://doi.org/10.1080/21655979.2021.2003665
Wikandari, Rachma, et al. "Application of cell culture technology and genetic engineering for production of future foods and crop improvement to strengthen food security." Bioengineered vol. 12,2 (2021): 11305-11330. doi: https://doi.org/10.1080/21655979.2021.2003665
Wikandari R, Manikharda, Baldermann S, Ningrum A, Taherzadeh MJ. Application of cell culture technology and genetic engineering for production of future foods and crop improvement to strengthen food security. Bioengineered. 2021 Dec;12(2):11305-11330. doi: 10.1080/21655979.2021.2003665. PMID: 34779353.
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A Deep Learning Model to Predict Knee Osteoarthritis Based on Nonimage Longitudinal Medical Record.

Journal of multidisciplinary healthcare

Ningrum DNA, Kung WM, Tzeng IS, Yuan SP, Wu CC, Huang CY, Muhtar MS, Nguyen PA, Li JY, Wang YC.
PMID: 34539180
J Multidiscip Healthc. 2021 Sep 11;14:2477-2485. doi: 10.2147/JMDH.S325179. eCollection 2021.

PURPOSE: To develop deep learning model (Deep-KOA) that can predict the risk of knee osteoarthritis (KOA) within the next year by using the previous three years nonimage-based electronic medical record (EMR) data.PATIENTS AND METHODS: We randomly selected information of...

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Ningrum DNA, Kung WM, Tzeng IS, et al. A Deep Learning Model to Predict Knee Osteoarthritis Based on Nonimage Longitudinal Medical Record. J Multidiscip Healthc. 2021;14:2477-2485doi: 10.2147/JMDH.S325179.
Ningrum, D. N. A., Kung, W. M., Tzeng, I. S., Yuan, S. P., Wu, C. C., Huang, C. Y., Muhtar, M. S., Nguyen, P. A., Li, J. Y., & Wang, Y. C. (2021). A Deep Learning Model to Predict Knee Osteoarthritis Based on Nonimage Longitudinal Medical Record. Journal of multidisciplinary healthcare, 142477-2485. https://doi.org/10.2147/JMDH.S325179
Ningrum, Dina Nur Anggraini, et al. "A Deep Learning Model to Predict Knee Osteoarthritis Based on Nonimage Longitudinal Medical Record." Journal of multidisciplinary healthcare vol. 14 (2021): 2477-2485. doi: https://doi.org/10.2147/JMDH.S325179
Ningrum DNA, Kung WM, Tzeng IS, Yuan SP, Wu CC, Huang CY, Muhtar MS, Nguyen PA, Li JY, Wang YC. A Deep Learning Model to Predict Knee Osteoarthritis Based on Nonimage Longitudinal Medical Record. J Multidiscip Healthc. 2021 Sep 11;14:2477-2485. doi: 10.2147/JMDH.S325179. eCollection 2021. PMID: 34539180; PMCID: PMC8445097.
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Deep Learning Classifier with Patient's Metadata of Dermoscopic Images in Malignant Melanoma Detection.

Journal of multidisciplinary healthcare

Ningrum DNA, Yuan SP, Kung WM, Wu CC, Tzeng IS, Huang CY, Li JY, Wang YC.
PMID: 33907414
J Multidiscip Healthc. 2021 Apr 21;14:877-885. doi: 10.2147/JMDH.S306284. eCollection 2021.

BACKGROUND: Incidence of skin cancer is one of the global burdens of malignancies that increase each year, with melanoma being the deadliest one. Imaging-based automated skin cancer detection still remains challenging owing to variability in the skin lesions and...

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Ningrum DNA, Yuan SP, Kung WM, et al. Deep Learning Classifier with Patient's Metadata of Dermoscopic Images in Malignant Melanoma Detection. J Multidiscip Healthc. 2021;14:877-885doi: 10.2147/JMDH.S306284.
Ningrum, D. N. A., Yuan, S. P., Kung, W. M., Wu, C. C., Tzeng, I. S., Huang, C. Y., Li, J. Y., & Wang, Y. C. (2021). Deep Learning Classifier with Patient's Metadata of Dermoscopic Images in Malignant Melanoma Detection. Journal of multidisciplinary healthcare, 14877-885. https://doi.org/10.2147/JMDH.S306284
Ningrum, Dina Nur Anggraini, et al. "Deep Learning Classifier with Patient's Metadata of Dermoscopic Images in Malignant Melanoma Detection." Journal of multidisciplinary healthcare vol. 14 (2021): 877-885. doi: https://doi.org/10.2147/JMDH.S306284
Ningrum DNA, Yuan SP, Kung WM, Wu CC, Tzeng IS, Huang CY, Li JY, Wang YC. Deep Learning Classifier with Patient's Metadata of Dermoscopic Images in Malignant Melanoma Detection. J Multidiscip Healthc. 2021 Apr 21;14:877-885. doi: 10.2147/JMDH.S306284. eCollection 2021. PMID: 33907414; PMCID: PMC8071207.
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Survey data of COVID-19-related knowledge, attitude, and practices among indonesian undergraduate students.

Data in brief

Saefi M, Fauzi A, Kristiana E, Adi WC, Muchson M, Setiawan ME, Islami NN, Ningrum DEAF, Ikhsan MA, Ramadhani M.
PMID: 32607405
Data Brief. 2020 Jun 12;31:105855. doi: 10.1016/j.dib.2020.105855. eCollection 2020 Aug.

The dataset presented in this paper is an examination of COVID-19-related knowledge, attitude, and practice among Indonesian undergraduate students. The data were collected during first month of college or university closure due to COVID-19 through a survey distributed via...

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Saefi M, Fauzi A, Kristiana E, et al. Survey data of COVID-19-related knowledge, attitude, and practices among indonesian undergraduate students. Data Brief. 2020;31:105855doi: 10.1016/j.dib.2020.105855.
Saefi, M., Fauzi, A., Kristiana, E., Adi, W. C., Muchson, M., Setiawan, M. E., Islami, N. N., Ningrum, D. E. A. F., Ikhsan, M. A., & Ramadhani, M. (2020). Survey data of COVID-19-related knowledge, attitude, and practices among indonesian undergraduate students. Data in brief, 31105855. https://doi.org/10.1016/j.dib.2020.105855
Saefi, Muhammad, et al. "Survey data of COVID-19-related knowledge, attitude, and practices among indonesian undergraduate students." Data in brief vol. 31 (2020): 105855. doi: https://doi.org/10.1016/j.dib.2020.105855
Saefi M, Fauzi A, Kristiana E, Adi WC, Muchson M, Setiawan ME, Islami NN, Ningrum DEAF, Ikhsan MA, Ramadhani M. Survey data of COVID-19-related knowledge, attitude, and practices among indonesian undergraduate students. Data Brief. 2020 Jun 12;31:105855. doi: 10.1016/j.dib.2020.105855. eCollection 2020 Aug. PMID: 32607405; PMCID: PMC7291994.
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Showing 1 to 7 of 7 entries