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JAK inhibitors are effective in a subset of patients with juvenile dermatomyositis: a monocentric retrospective study.

Rheumatology (Oxford, England)

Le Voyer T, Gitiaux C, Authier FJ, Bodemer C, Melki I, Quartier P, Aeschlimann F, Isapof A, Herbeuval JP, Bondet V, Charuel JL, Frémond ML, Duffy D, Rodero MP, Bader-Meunier B.
PMID: 33576769
Rheumatology (Oxford). 2021 Dec 01;60(12):5801-5808. doi: 10.1093/rheumatology/keab116.

OBJECTIVE: To evaluate the efficacy and safety of Janus kinase inhibitors (JAKis) in JDM.METHODS: We conducted a single-centre retrospective study of patients with JDM treated by JAKi with a follow-up of at least 6 months. Proportion of clinically inactive...

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Le Voyer T, Gitiaux C, Authier FJ, et al. JAK inhibitors are effective in a subset of patients with juvenile dermatomyositis: a monocentric retrospective study. Rheumatology (Oxford). 2021;60(12):5801-5808doi: 10.1093/rheumatology/keab116.
Le Voyer, T., Gitiaux, C., Authier, F. J., Bodemer, C., Melki, I., Quartier, P., Aeschlimann, F., Isapof, A., Herbeuval, J. P., Bondet, V., Charuel, J. L., Frémond, M. L., Duffy, D., Rodero, M. P., & Bader-Meunier, B. (2021). JAK inhibitors are effective in a subset of patients with juvenile dermatomyositis: a monocentric retrospective study. Rheumatology (Oxford, England), 60(12), 5801-5808. https://doi.org/10.1093/rheumatology/keab116
Le Voyer, Tom, et al. "JAK inhibitors are effective in a subset of patients with juvenile dermatomyositis: a monocentric retrospective study." Rheumatology (Oxford, England) vol. 60,12 (2021): 5801-5808. doi: https://doi.org/10.1093/rheumatology/keab116
Le Voyer T, Gitiaux C, Authier FJ, Bodemer C, Melki I, Quartier P, Aeschlimann F, Isapof A, Herbeuval JP, Bondet V, Charuel JL, Frémond ML, Duffy D, Rodero MP, Bader-Meunier B. JAK inhibitors are effective in a subset of patients with juvenile dermatomyositis: a monocentric retrospective study. Rheumatology (Oxford). 2021 Dec 01;60(12):5801-5808. doi: 10.1093/rheumatology/keab116. PMID: 33576769.
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A Comparison of Clinicopathologic Outcomes Across Neoadjuvant and Adjuvant Treatment Modalities in Resectable Gastric Cancer.

JAMA network open

Anderson E, LeVee A, Kim S, Atkins K, Guan M, Placencio-Hickok V, Moshayedi N, Hendifar A, Osipov A, Gangi A, Burch M, Waters K, Cho M, Klempner S, Chao J, Kamrava M, Gong J.
PMID: 34889947
JAMA Netw Open. 2021 Dec 01;4(12):e2138432. doi: 10.1001/jamanetworkopen.2021.38432.

IMPORTANCE: Treatment of resectable gastric cancer (RGC) uses a multimodal approach, including surgical treatment and chemotherapy with or without radiation therapy, and the optimal treatment strategy and timing of each of these modalities is unknown.OBJECTIVE: To investigate the association...

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Anderson E, LeVee A, Kim S, et al. A Comparison of Clinicopathologic Outcomes Across Neoadjuvant and Adjuvant Treatment Modalities in Resectable Gastric Cancer. JAMA Netw Open. 2021;4(12):e2138432doi: 10.1001/jamanetworkopen.2021.38432.
Anderson, E., LeVee, A., Kim, S., Atkins, K., Guan, M., Placencio-Hickok, V., Moshayedi, N., Hendifar, A., Osipov, A., Gangi, A., Burch, M., Waters, K., Cho, M., Klempner, S., Chao, J., Kamrava, M., & Gong, J. (2021). A Comparison of Clinicopathologic Outcomes Across Neoadjuvant and Adjuvant Treatment Modalities in Resectable Gastric Cancer. JAMA network open, 4(12), e2138432. https://doi.org/10.1001/jamanetworkopen.2021.38432
Anderson, Eric, et al. "A Comparison of Clinicopathologic Outcomes Across Neoadjuvant and Adjuvant Treatment Modalities in Resectable Gastric Cancer." JAMA network open vol. 4,12 (2021): e2138432. doi: https://doi.org/10.1001/jamanetworkopen.2021.38432
Anderson E, LeVee A, Kim S, Atkins K, Guan M, Placencio-Hickok V, Moshayedi N, Hendifar A, Osipov A, Gangi A, Burch M, Waters K, Cho M, Klempner S, Chao J, Kamrava M, Gong J. A Comparison of Clinicopathologic Outcomes Across Neoadjuvant and Adjuvant Treatment Modalities in Resectable Gastric Cancer. JAMA Netw Open. 2021 Dec 01;4(12):e2138432. doi: 10.1001/jamanetworkopen.2021.38432. PMID: 34889947.
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Aβ initiates brain hypometabolism, network dysfunction and behavioral abnormalities via NOX2-induced oxidative stress in mice.

Communications biology

Malkov A, Popova I, Ivanov A, Jang SS, Yoon SY, Osypov A, Huang Y, Zilberter Y, Zilberter M.
PMID: 34504272
Commun Biol. 2021 Sep 09;4(1):1054. doi: 10.1038/s42003-021-02551-x.

A predominant trigger and driver of sporadic Alzheimer's disease (AD) is the synergy of brain oxidative stress and glucose hypometabolism starting at early preclinical stages. Oxidative stress damages macromolecules, while glucose hypometabolism impairs cellular energy supply and antioxidant defense....

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Malkov A, Popova I, Ivanov A, et al. Aβ initiates brain hypometabolism, network dysfunction and behavioral abnormalities via NOX2-induced oxidative stress in mice. Commun Biol. 2021;4(1):1054doi: 10.1038/s42003-021-02551-x.
Malkov, A., Popova, I., Ivanov, A., Jang, S. S., Yoon, S. Y., Osypov, A., Huang, Y., Zilberter, Y., & Zilberter, M. (2021). Aβ initiates brain hypometabolism, network dysfunction and behavioral abnormalities via NOX2-induced oxidative stress in mice. Communications biology, 4(1), 1054. https://doi.org/10.1038/s42003-021-02551-x
Malkov, Anton, et al. "Aβ initiates brain hypometabolism, network dysfunction and behavioral abnormalities via NOX2-induced oxidative stress in mice." Communications biology vol. 4,1 (2021): 1054. doi: https://doi.org/10.1038/s42003-021-02551-x
Malkov A, Popova I, Ivanov A, Jang SS, Yoon SY, Osypov A, Huang Y, Zilberter Y, Zilberter M. Aβ initiates brain hypometabolism, network dysfunction and behavioral abnormalities via NOX2-induced oxidative stress in mice. Commun Biol. 2021 Sep 09;4(1):1054. doi: 10.1038/s42003-021-02551-x. PMID: 34504272; PMCID: PMC8429759.
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Associations between tumor and edema volumes with tumor infiltrating lymphocytes in brain metastasis - A preliminary study.

Clinical neurology and neurosurgery

Meyer HJ, Höhn AK, Prasse G, Hoffmann KT, Surov A.
PMID: 34915356
Clin Neurol Neurosurg. 2021 Dec 08;212:107088. doi: 10.1016/j.clineuro.2021.107088. Epub 2021 Dec 08.

OBJECTIVE: Perifocal edema of brain tumors is associated with survival and neurological symptoms. The present study sought to elucidate the association between edema volume and tumor infiltrating lymphocytes (TIL) in brain metastasis.METHODS: 25 patients with brain metastasis were included...

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Meyer HJ, Höhn AK, Prasse G, et al. Associations between tumor and edema volumes with tumor infiltrating lymphocytes in brain metastasis - A preliminary study. Clin Neurol Neurosurg. 2021;212:107088doi: 10.1016/j.clineuro.2021.107088.
Meyer, H. J., Höhn, A. K., Prasse, G., Hoffmann, K. T., & Surov, A. (2021). Associations between tumor and edema volumes with tumor infiltrating lymphocytes in brain metastasis - A preliminary study. Clinical neurology and neurosurgery, 212107088. https://doi.org/10.1016/j.clineuro.2021.107088
Meyer, Hans-Jonas, et al. "Associations between tumor and edema volumes with tumor infiltrating lymphocytes in brain metastasis - A preliminary study." Clinical neurology and neurosurgery vol. 212 (2021): 107088. doi: https://doi.org/10.1016/j.clineuro.2021.107088
Meyer HJ, Höhn AK, Prasse G, Hoffmann KT, Surov A. Associations between tumor and edema volumes with tumor infiltrating lymphocytes in brain metastasis - A preliminary study. Clin Neurol Neurosurg. 2021 Dec 08;212:107088. doi: 10.1016/j.clineuro.2021.107088. Epub 2021 Dec 08. PMID: 34915356.
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Mining and Tailings Dam Detection in Satellite Imagery Using Deep Learning.

Sensors (Basel, Switzerland)

Balaniuk R, Isupova O, Reece S.
PMID: 33291634
Sensors (Basel). 2020 Dec 04;20(23). doi: 10.3390/s20236936.

This work explores the combination of free cloud computing, free open-source software, and deep learning methods to analyze a real, large-scale problem: the automatic country-wide identification and classification of surface mines and mining tailings dams in Brazil. Locations of...

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Balaniuk R, Isupova O, Reece S. Mining and Tailings Dam Detection in Satellite Imagery Using Deep Learning. Sensors (Basel). 2020;20(23)doi: 10.3390/s20236936.
Balaniuk, R., Isupova, O., & Reece, S. (2020). Mining and Tailings Dam Detection in Satellite Imagery Using Deep Learning. Sensors (Basel, Switzerland), 20(23), . https://doi.org/10.3390/s20236936
Balaniuk, Remis, et al. "Mining and Tailings Dam Detection in Satellite Imagery Using Deep Learning." Sensors (Basel, Switzerland) vol. 20,23 (2020). doi: https://doi.org/10.3390/s20236936
Balaniuk R, Isupova O, Reece S. Mining and Tailings Dam Detection in Satellite Imagery Using Deep Learning. Sensors (Basel). 2020 Dec 04;20(23). doi: 10.3390/s20236936. PMID: 33291634; PMCID: PMC7731393.
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Showing 289 to 293 of 293 entries