Objective To study the effects of chronic manganism on hearing and cochlear cells in rats by using animal model of chronic manganism .Methods Sixty adult SD rats were randomly divided into Mn - exposed and controlgroups.RatsweretreatedwithMnCl24H2O(100mg·kg -1·d-1)ordeionizedwaterbygastricperfusion, lasted for 12 weeks .The Mn concentration in peripheral blood was measured respectively at 4 weeks ,8 weeks and 12 weeks after treatment .At 12 weeks after treatment ,the auditory brainstem response was recorded ,the hair cells morphology and counting were examined by stretched preparation of basilar membrane stained with FITC -phalloi-din ,and the spiral ganglion cells morphology and counting were studied by HE staining ,the ultrastructure changes of hair cells and spiral ganglion cells were detected by transmission electron microscopy .Results The blood Mn concentration increased gradually with time after treatment .ABR thresholds at 4 ,8 ,16 ,24 and 32 kHz were sig-nificantly increased at 12 weeks after treatment ,especially in the high-frequency range .Morphological study at 12 weeks after treatment showed loss of outer hair cells ,mainly in the basal turn of the cochlea ,and decreased number of spiral ganglion cells .The ultrastructure changes of outer hair cells and spiral ganglion cells included the break -ups ,disappearance or vacuolar change of mitochondria cristas .Conclusion Our data demonstrate that chronic man-ganism can cause loss of outer hair cells and spiral ganglion cells in cochlear in rats ,leading to hearing loss .

At present, implant surgery robots have basically achieved "surgical intelligence", but "brain-inspired intelligence" of robots is still in the stage of theory and exploration. The formulation of a clinical implantation plan depends on the timing of implantation, implantation area, bone condition, surgical procedure, patient factors, etc., which need to evaluate the corresponding clinical decision indicators and clinical pathways. Inspired by evidence-based medicine and the potential of big data and deep learning, combined with the data characteristics of clinical decision indicators and clinical pathways that can be quantitatively or qualitatively analyzed, this review simulates the cognitive behavior and neural mechanisms of the human brain and proposes a feasible brain-inspired intelligence scheme by predicting the decision indices and executing clinical pathways intelligently, that is, "select clinical indicators and clarify clinical pathways -- construct database -- use deep learning to intelligently predict decision indicators -- intelligent execution of clinical pathways -- brain-inspired intelligence of implant decision-making". Combined with the previous research results of our team, this review also describes the process of realization of brain-inspired intelligence for immediate implant timing decisions, providing an example of the comprehensive realization of brain-inspired intelligence of implant surgery robots in the future. In the future, how to excavate and summarize other clinical decision factors and select the best way to realize the automatic prediction of evidence-based clinical indicators and pathways and finally realize the complete intellectualization of clinical diagnosis and treatment processes will be one of the directions that dental clinicians need to strive for.