Cyclometalated gold(III)-hydride under oriented external electric fields: a new strategy to modulate its reactivity?

Selected gold complexes have been regarded as promising anti-cancer agents because they can bind with protein targets containing thiol or selenol moieties, but their clinical applications were hindered by the unbiased binding towards off-target thiol-proteins. Recently, a novel gold(III)-hydride complex (abbreviated as 1) with visible light-induced thiol reactivity has been reported as potent photo-activated anticancer agents (Angew. Chem. Int. Ed., 2020, 132, 11139). To explore new strategies to stimuli this potential antitumor drug, the effect of oriented external electric fields (OEEFs) on its geometric structure, electronic properties, and chemical reactivity was systematically investigated. Results reveal that imposing external electric fields along the Au-H bond of 1 can effectively activate this bond, which is conducive to its dissociation and the binding of Au site to potential targets. Hence, this study provides a new OEEF-strategy to activate this reported gold(III)-hydride, revealing its potential application in electrochemical therapy. We anticipate this work could promote the development of more electric field-activated anticancer agents. However, further experimental research should be conducted to verify the conclusions obtained in this work.

Risk factors and predictive model of adrenocortical insufficiency in patients with traumatic brain injury.

BACKGROUND: Neuroendocrine dysfunction after traumatic brain injury (TBI) has received increased attention due to its impact on the recovery of neural function. The purpose of this study is to investigate the incidence and risk factors of adrenocortical insufficiency (AI) after TBI to reveal independent predictors and build a prediction model of AI after TBI. METHODS: Enrolled patients were grouped into the AI and non-AI groups. Fourteen preset impact factors were recorded. Patients were regrouped according to each impact factor as a categorical variable. Univariate and multiple logistic regression analyses were performed to screen the related independent risk factors of AI after TBI and develop the predictive model. RESULTS: A total of 108 patients were recruited, of whom 34 (31.5%) patients had AI. Nine factors (age, Glasgow Coma Scale [GCS] score on admission, mean arterial pressure [MAP], urinary volume, serum sodium level, cerebral hernia, frontal lobe contusion, diffuse axonal injury [DAI], and skull base fracture) were probably related to AI after TBI. Three factors (urinary volume [X 4], serum sodium level [X 5], and DAI [X 8]) were independent variables, based on which a prediction model was developed (logit P= -3.552+2.583X 4+2.235X 5+2.269X 8). CONCLUSIONS: The incidence of AI after TBI is high. Factors such as age, GCS score, MAP, urinary volume, serum sodium level, cerebral hernia, frontal lobe contusion, DAI, and skull base fracture are probably related to AI after TBI. Urinary volume, serum sodium level, and DAI are the independent predictors of AI after TBI.