Identification and functional protection of parathyroid glands are the key to reduce the incidence of postoperative complications after thyroid surgery. In recent years, the development of several fluorescence imaging technology and the application of artificial intelligence based on deep learning in thyroid surgery have brought technical breakthroughs in the identification and blood supply assessment of parathyroid glands during surgery, helping surgeons to identify parathyroid glands quickly and accurately, and improving the prognosis of surgery. Based on this, this article focuses on the new advances in the identification and protection of parathyroid glands in thyroid surgery, especially the research and application progress of fluorescence imaging, lymph node tracers, artificial intelligence and other aspects, and discusses the future development prospects.

Identification and functional protection of parathyroid glands are the key to reduce the incidence of postoperative complications after thyroid surgery. In recent years, the development of several fluorescence imaging technology and the application of artificial intelligence based on deep learning in thyroid surgery have brought technical breakthroughs in the identification and blood supply assessment of parathyroid glands during surgery, helping surgeons to identify parathyroid glands quickly and accurately, and improving the prognosis of surgery. Based on this, this article focuses on the new advances in the identification and protection of parathyroid glands in thyroid surgery, especially the research and application progress of fluorescence imaging, lymph node tracers, artificial intelligence and other aspects, and discusses the future development prospects.

Objective:To explore the predictive value of amplitude integrated electroencephalography(aEEG)in the neurological prognosis of children with neonatal bacterial meningitis(NBM).Methods:The clinical data and aEEG results from 148 children diagnosed with NBM who completed aEEG examinations in the Department of Neonatology at Kunming Children′s Hospital from January 2018 to December 2019 were retrospectively analyzed.According to whether aEEG is abnormal, the children were divided into aEEG abnormal group and aEEG non-abnormal group.According to the degree of aEEG abnormality, children with aEEG abnormality were divided into aEEG mild abnormal group and aEEG severe abnormal group.The abnormal rate and abnormal characteristics of aEEG were analyzed; The clinical data of two groups were compared.Results:(1)Among the 148 children with NBM, 49 children had abnormal aEEG, 99 children had no abnormality, and the aEEG abnormal rate was 33.1%.The abnormal aEEG was manifested as delayed sleep-wake cycle maturation in 39 (26.3%) cases, abnormal discharge in eight (5.4%) cases, and abnormal background activity in one (0.6%) case.(2)The proportion of children with convulsive seizures and refractory NBM in aEEG abnormal group were significantly higher than those in aEEG non-abnormal group ( P<0.05). In the routine and biochemical abnormal indexes of cerebrospinal fluid, the proportion of protein >3 g/L, cerebrospinal fluid leukocyte>500×10 6/L, cerebrospinal fluid glucose<1.5 mmol/L, positive cerebrospinal fluid culture, positive blood and cerebrospinal fluid culture, abnormal head MRI in aEEG abnormal group significantly increased ( P<0.05); While there was no significant difference regarding blood routine leukocyte abnormality, CRP increase, and positive blood culture ratio between two groups ( P>0.05). (3) 148 cases of NBM children were followed up to 15 months old, 119 (80.4%) cases completed the follow-up, the loss rate was 19.6%, three cases died, and 11 cases had psychomotor retardation.Compared with the children with abnormal aEEG, the prognosis of children with NBM was significantly different, the Spearman rank correlation coefficient r was 0.315 ( P<0.05). COX regression was used to analyze the predictive value of each index for adverse outcomes. Abnormal aEEG was an independent risk factor for adverse outcomes in children with NBM ( OR=7.452, 95% CI 1.605-34.591, P<0.05). Conclusion:The aEEG monitoring of children with NBM, if abnormal, may indicate severe NBM, which is likely to be transformed into refractory NBM or has a poor prognosis.

Librarians play a key role in the library information ecosystem.Librarians and library users interact and influence each other in process and use of information.Tagging defined by network users is used in description of words and phrases in different information resources.When it is used in library, user-oriented service will become the target of information service, and the role of information service persons, information organization methods and information low efficiency will change.However, rational planning of ecosystem, rational control of tagging, and improvement of librarian information literacy can reduce the negative effect of tagging.