Ping Li¹, Lindong Cheng², Chunhua Liao³, Jianhua Xia⁴, Li Tan⁵

¹Graduate School, Wannan Medical College, Anhui 241000, China. ²Graduate School, Hebei North University, Hebei 075000, China. ³School of Anesthesiology, Naval Medical University, Shanghai 200433, China. ⁴Department of Anesthesiology, Shanghai Pudong New District People's Hospital, Shanghai 200433, China. ⁵Department of Anesthesiology, Chongqing University Cancer Hospital, Chongqing 400030, China.

Address correspondence to: Li Tan, Department of Anesthesiology, Chongqing University Cancer Hospital, No.181 Hanyu Road, Chongqing 400030, China. E-mail: tanlihh@163.com.

Received July 18, 2023; Accepted September 11, 2023; Published September 30, 2023

DOI: https://doi.org/10.61189/550782gbbqxs

Highlights

● Risk of invasive candida infection and its related mortality are increasing significantly in perioperative patients.

● C-type lectin receptors are the primary pattern-recognition receptors for fungi-induced host defense and innate immune activation.

● Protein post-translational modifications are one of the core factors in host innate immune regulation.

● Post-translational modifications sites on proteins are anticipated to serve as potential targets for modulating anti-fungal immunity.

Jinjing Wu^1,*, Yang Yuan^2,*, Long Liu¹, Haipo Cui¹, Tianying Xu³, Miao Zhou⁴, Zhanheng Chen³, Bing Xu³

¹School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China. ²School of Computer Science and Artificial Intelligence, Changzhou University, Jiangsu 213164, China. ³School of Anesthesiology, Second Military Medical University/Naval Medical University, Shanghai 200433, China. ⁴Department of Anesthesiology, the Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University, Nanjing 210009, Jiangsu, China. 

^*The authors contribute equally.

Address correspondence to: Haipo Cui, School of Health Science and Engineering, University of Shanghai for Science and Technology, NO.516, Jungong Road, Shanghai 200093, China. E-mail: h_b_cui@163.com, Tel: +86-21-55271290; Bing Xu, School of Anesthesiology, Second Military Medical University/Naval Medical University, 800 Xiangyin Road, Shanghai 200433, China. E-mail: mzxubing1992@163.com, Tel: +86-21-81872030; Zhanheng Chen, School of Anesthesiology, Second Military Medical University/Naval Medical University, 800 Xiangyin Road, Shanghai 200433, China. E-mail: chenzhanheng17@mails.ucas.ac.cn, Tel: +86 21 81872034. 

Received July 19, 2023; Accepted September 6, 2023; Published September 30, 2023

DOI: https://doi.org/10.61189/663074tcakcn

Highlights

● Medical endoscopic images can provide doctors with more accurate, visualized, and three-dimensional views of various internal tissues.

● Image processing techniques such as image denoising, image deblurring, image enhancement, and image segmentation can improve the imaging quality of endoscopes.

Long Liu¹, Xiaobo Zhu³, Jinjing Wu¹, Qianyuan Hu¹, Haipo Cui¹, Zhanheng Chen², Tianying Xu²

¹School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China. ²School of Anesthesiology, Second Military Medical University/Naval Medical University, Shanghai 200433, China. ³College of Electronic and Information Engineering, Tongji University, Shanghai 201804, China.

Address correspondence to: Haipo Cui, School of Health Science and Engineering, University of Shanghai for Science and Technology, NO.516, Jungong Road, Shanghai 200093, China. Tel: +86-21-55271290, E-mail: h_b_cui@163.com; Zhanheng Chen, School of Anesthesiology, Second Military Medical University/Naval Medical University, 800 Xiangyin Road, Shanghai 200433, China. Tel: +86 21 81872034, E-mail: chenzhanheng17@mails.ucas.ac.cn; Tianying Xu, School of Anesthesiology, Second Military Medical University/Naval Medical University, 800 Xiangyin Road, Shanghai 200433, China. Tel: +86 21 81872029, E-mail: xty7910@163.com.

Received July 19, 2023; Accepted September 7, 2023; Published September 30, 2023

DOI: https://doi.org/10.61189/803479emewvv

Highlights

● The development history of convolutional neural networks and the transition to graph convolutional networks are introduced, as well as the evolution of network layers.

● Graph convolutional networks have been widely demonstrated to be applicable in various perioperative medical image processing scenarios.

● This is the first comprehensive review of the applications of graph convolutional networks in image segmentation, image reconstruction, disease prediction, lesion detection and localization, disease classification and diagnosis, and surgical interventions.

Yanchen Lin¹, Jing Huang², Ying Zhang¹, Houfeng Li¹, Huixiu Hu¹, Li Tan³

¹Graduate School, Hebei North University, Zhangjiakou 075000, Hebei, China. ²Graduate School, Wannan Medical College, Wuhu 241002, Anhui, China. ³Department of Anesthesiology, Chongqing University Cancer Hospital, Chongqing 400030, China.

Address correspondence to: Li Tan, Department of Anesthesiology, Chongqing University Cancer Hospital, No.181 Hanyu Road, Chongqing 400030, China. E-mail: tanlihh@163.com.

Received August 24, 2023; Accepted September 7, 2023; Published September 30, 2023

DOI: https://doi.org/10.61189/377184mkfywu

Highlights

● The measurement of central venous pressure in patients diagnosed with septic shock does not yield prognostic improvements.

● Central venous pressure measurement in patients with septic shock is associated with prolonged ICU stay. 

● Central venous pressure measurement is not advised for patients diagnosed with septic shock.