The Effect of Ceruloplasmin Against Ischemia-Reperfusion Injury in Epigastric Island Flap in Rats

Seyid, Mircafer; Tiftikçioğlu, Yiğit Özer; Erdem, Mehmet; Akdemır, Ovunc; Tatar, Burak Ergün; Uyanıkgil, Yiğit; Ercan, Gülinnaz

doi:10.1016/j.jss.2021.05.045

Cited by 4 publications

(3 citation statements)

References 39 publications

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“…At the same time, Chang et al [ 35 ] recommended that the microvascular tissue reconstruction should be performed with full discretion of patients with high BMI. Additionally, prolonged ischemia time of the free flap and subsequent ischemia-reperfusion injury can also increase the risk of postoperative complications and eventually flap failure[ 36 ].…”

Section: Discussionmentioning

confidence: 99%

Flap failure prediction in microvascular tissue reconstruction using machine learning algorithms

Shi¹,

Li²,

Li³

et al. 2022

WJCC

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BACKGROUND Microvascular tissue reconstruction is a well-established, commonly used technique for a wide variety of the tissue defects. However, flap failure is associated with an additional hospital stay, medical cost burden, and mental stress. Therefore, understanding of the risk factors associated with this event is of utmost importance. AIM To develop machine learning-based predictive models for flap failure to identify the potential factors and screen out high-risk patients. METHODS Using the data set of 946 consecutive patients, who underwent microvascular tissue reconstruction of free flap reconstruction for head and neck, breast, back, and extremity, we established three machine learning models including random forest classifier, support vector machine, and gradient boosting. Model performances were evaluated by the indicators such as area under the curve of receiver operating characteristic curve, accuracy, precision, recall, and F1 score. A multivariable regression analysis was performed for the most critical variables in the random forest model. RESULTS Post-surgery, the flap failure event occurred in 34 patients (3.6%). The machine learning models based on various preoperative and intraoperative variables were successfully developed. Among them, the random forest classifier reached the best performance in receiver operating characteristic curve, with an area under the curve score of 0.770 in the test set. The top 10 variables in the random forest were age, body mass index, ischemia time, smoking, diabetes, experience, prior chemotherapy, hypertension, insulin, and obesity. Interestingly, only age, body mass index, and ischemic time were statistically associated with the outcomes. CONCLUSION Machine learning-based algorithms, especially the random forest classifier, were very important in categorizing patients at high risk of flap failure. The occurrence of flap failure was a multifactor-driven event and was identified with numerous factors that warrant further investigation. Importantly, the successful application of machine learning models may help the clinician in decision-making, understanding the underlying pathologic mechanisms of the disease, and improving the long-term outcome of patients.

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Section: Discussionmentioning

confidence: 99%

Flap failure prediction in microvascular tissue reconstruction using machine learning algorithms

Shi¹,

Li²,

Li³

et al. 2022

WJCC

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“…It is synthesized by the liver and benefits cardiac function in ischemic cardiomyopathy. [ 145,146 ] An artificial copper‐containing protein was designed with a function similar to ceruloplasmin. In a groundbreaking study, Zhang et al.…”

Section: Nitric Oxide‐inspired Strategy For Treating Myocardial Ische...mentioning

confidence: 99%

“…It is synthesized by the liver and benefits cardiac function in ischemic cardiomyopathy. [145,146] An artificial copper-containing protein was designed with a function similar to ceruloplasmin. In a groundbreaking study, Zhang et al reported biomimetic nanocells by integrating hypoxic stem cells, cell membranes, and copper-containing ferritin nanocages (Fth-Cu).…”

Section: Nitric Oxide-inspired Strategy For Treating Myocardial Ische...mentioning

confidence: 99%

Nanomedicine‐Based Therapeutics for Myocardial Ischemic/Reperfusion Injury

Yang

et al. 2023

Adv Healthcare Materials

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Myocardial ischemic/reperfusion (IR) injury is a global cardiovascular disease with high mortality and morbidity. Therapeutic interventions for myocardial ischemia involve restoring the occluded coronary artery. However, reactive oxygen species (ROS) inevitably impair the cardiomyocytes during the ischemic and reperfusion phases. Antioxidant therapy holds great promise against myocardial IR injury. The current therapeutic methodologies for ROS scavenging depend predominantly on administering antioxidants. Nevertheless, the intrinsic drawbacks of antioxidants limit their further clinical transformation. The use of nanoplatforms with versatile characteristics greatly benefits drug delivery in myocardial ischemic therapy. Nanoplatform‐mediated drug delivery significantly improves drug bioavailability, increases therapeutic index, and reduces systemic toxicity. Nanoplatforms can be specifically and reasonably designed to enhance molecule accumulation at the myocardial site. The present review initially summarizes the mechanism of ROS generation during the process of myocardial ischemia. The understanding of this phenomenon will facilitate the advancement of innovative therapeutic strategies against myocardial IR injury. The latest developments in nanomedicine for treating myocardial ischemic injury are then discussed. Finally, the current challenges and perspectives in antioxidant therapy for myocardial IR injury are addressed.

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Propionyl-l-carnitine mitigates ischemia-reperfusion injury in rat epigastric island flaps

Eyuboglu,

Akdemir,

Erbas

et al. 2024

Heliyon

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The Effect of Ceruloplasmin Against Ischemia-Reperfusion Injury in Epigastric Island Flap in Rats

Cited by 4 publications

References 39 publications

Flap failure prediction in microvascular tissue reconstruction using machine learning algorithms

Flap failure prediction in microvascular tissue reconstruction using machine learning algorithms

Nanomedicine‐Based Therapeutics for Myocardial Ischemic/Reperfusion Injury

Propionyl-l-carnitine mitigates ischemia-reperfusion injury in rat epigastric island flaps

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