Novel PHD2/HDACs hybrid inhibitors protect against cisplatin-induced acute kidney injury

The preventative effect of Baihe Gujin Pill on cisplatin-induced acute kidney injury by activating the PI3K/AKT and suppressing the NF-κB/MAPK pathways

ETHNOPHARMACOLOGICAL RELEVANCE

Baihe Gujin Pill (BHGJP) is a traditional Chinese medicine (TCM) derived from the "Collection of Medical Formulas". BHGJP is applied to treat lung and kidney deficiency by nourishing yin and clearing heat. However, the role and preventative mechanism of BHGJP in cisplatin induced acute kidney injury (CIAKI) are poorly understood.

AIM OF THE STUDY

The preventative effect of BHGJP on CIAKI by the in vitro and in vivo experiments based on network pharmacology was investigated.

METHODS

Network pharmacology was used to predict the protective effect of BHGJP on CIAKI. The effect and mechanism of BHGJP against CIAKI were detected and verified by the in vitro kidney cells 293T and HK-2 as well as the in vivo mice model established by a single injection of cisplatin.

RESULTS

Network pharmacology predicted that BHGJP prevented CIAKI by regulating PI3K/AKT and NF-κB/MAPK signaling pathways. BHGJP could reverse the reduced cell viability of HK-2 and 293T cells caused by cisplatin without decreasing its cytotoxic effects on H460, H1299, and A549 cells. Meanwhile, BHGJP effectively controlled kidney injury in the CIAKI model. Moreover, cisplatin induced cell apoptosis and accumulation of reactive oxygen species (ROS) were downregulated after treatment with BHGJP. The changes of oxidative stress indexes of GSH, MDA, and SOD as well as the inflammatory factors of TNF-α, IL-6, and IL-1β in the CIAKI model were recovered to normal state when BHGJP treatment. Furthermore, BHGJP activated PI3K/AKT pathway and suppressed the NF-κB/MAPK pathway in the CIAKI model.

CONCLUSION

The study found that BHGJP prevented CIAKI by inhibiting apoptosis, oxidative stress, and inflammation via regulating PI3K/AKT and NF-κB/MAPK pathways, providing new efficacy and clinical applications for BHGJP.

Machine learning for acute kidney injury: Changing the traditional disease prediction mode

Acute kidney injury (AKI) is a serious clinical comorbidity with clear short-term and long-term prognostic implications for inpatients. The diversity of risk factors for AKI has been recognized in previous studies, and a series of predictive models have been developed using traditional statistical methods in conjunction with its preventability, but they have failed to meet the expectations in limited clinical applications, the rapid spread of electronic health records and artificial intelligence machine learning technology has brought new hope for the construction of AKI prediction models. In this article, we systematically review the definition and classification of machine learning methods, modeling ideas and evaluation methods, and the characteristics and current status of modeling studies. According to the modeling objectives, we subdivided them into critical care medical setting models, all medical environment models, special surgery models, special disease models, and special nephrotoxin exposure models. As the first review article to comprehensively summarize and analyze machine learning prediction models for AKI, we aim to objectively describe the advantages and disadvantages of machine learning approaches to modeling, and help other researchers more quickly and intuitively understand the current status of modeling research, inspire ideas and learn from experience, so as to guide and stimulate more research and more in-depth exploration in the future, which will ultimately provide greater help to improve the overall status of AKI diagnosis and treatment.

Improving lipophilicity of 5-(1-acetyl-5-phenylpyrazolidin-3-ylidene)-1,3-dimethylbarbituric acid increases its efficacy to activate hypoxia-inducible factors

Hypoxia-inducible factor (HIF) activators aid the treatment of renal anemia and ischemia. Recently, PyrzA (5-(1-acetyl-5-phenylpyrazolidin-3-ylidene)-1,3-dimethylbarbituric acid), a HIF activator by PHD inhibition without a 2-oxoglutarate moiety was reported. However, PyrzA has low lipophilicity, and it was necessary to improve its solubility by synthesizing derivatives. In this study, we synthesized and evaluated a higher lipophilic derivative of PyrzA and found that it exhibited higher HIF activity and stabilizing ability at low concentrations compared to Roxadustat, a commercially available HIF activator.