ABSTRACT
A low-power capacitorless demultiplexer-based multi-voltage domain low-dropout regulator (MVD-LDO) with 180 nm CMOS technology is proposed in this work. The MVD-LDO has a 1.5 V supply voltage headroom and regulates an output from four voltage domains ranging from 0.8 V to 1.4 V, with a high current efficiency of 99.98% with quiescent current of 53 µA with the aid of an integrated low-power demultiplexer controller which consumes only 68.85 pW. The fabricated chip has an area of 0.149 mm2 and can deliver up to 400 mA of current. The MVD-LDO's line and load regulations are 1.85 mV/V and 0.0003 mV/mA for the low-output voltage domain and 3.53 mV/V and 0.079 mV/mA for the high-output voltage domain. The LDO consumes only 174.5 µW in standby mode, making it suitable for integrating with an RF energy harvester chip to power sensor nodes.
ABSTRACT
BACKGROUND: The ability to hold an endoscope is an important skill for surgeons and assistants performing endoscopic neurosurgery. Motion tracking can provide an objective assessment for surgical skills and may aid in endoscopic neurosurgery. We developed a cost-effective system to study the feasibility of objectively distinguishing performance levels for operating an endoscope. METHODS: The study was divided into 2 parts. First, a video motion tracking analysis tool was built based on a printed mark and free software (Kinovea 0.8.15). Second, the tool was used to distinguish the holding endoscope performance of the robotic arm by experts (surgeon, n = 3) and novice users (residents, n = 6) under both 0' and 30' endoscopes. RESULTS: Through the printed mark and free software, we successfully built a system for video motion tracking. The data analysis showed that for both 0' and 30' endoscopes, the experts had a shorter total distance and depth, smaller average speed and maximum acceleration, and a fewer number of extreme accelerations than their novice counterparts. Compared with experts and residents, the fixed arm had better results. CONCLUSIONS: The simple low-cost video motion tracking system can provide an objective assessment of an endoscope holding skill, which allows for discrimination between an expert and a novice, and can be used by clinical neurosurgeons to select a qualified assistant.
Subject(s)
Endoscopes , Neurosurgical Procedures , Feasibility Studies , HumansABSTRACT
Background: Gastric cancer, especially intestinal-type gastric cancer, is considered as the result of the process of non-atrophic gastritis-atrophic gastritis-dysplasia-carcinogenesis. Aims: To explore the phenotypic characteristics and differentially expressed genes (DEGs) enrichment pathway of inflammatory cells between gastritis that prone to canceration (atrophic gastritis) and gastritis that not prone to canceration (non-atrophic gastritis). Methods: The datasets of GSE2669, GSE83389, GSE106656 and GSE27411 were downloaded from GEO database. DEGs were screened by R language and verified by GSE116312 dataset. DEGs screened from 3 datasets of 'non-atrophic gastritis-atrophic gastritis' were overlapped with inflammatory cell phenotypic characteristic genes. REACTOME and KEGG analyses of DEGs were performed. Results: A variety of DEGs in the 'normal gastric mucosa-non-atrophic gastritis-atrophic gastritis' dynamic process were screened, and 5 common genes were verified by GSE116312 dataset. A total of 85 inflammatory cell phenotypic characteristic genes were screened from 3 datasets. The percentage of neutrophil was high during 'normal gastric mucosa-non-atrophic gastritis' process while the percentages of fibroblast and macrophage were high during 'non-atrophic gastritis-atrophic gastritis' process. REACTOME and KEGG analyses showed that DEGs of inflammatory cell phenotype during 'non-atrophic gastritis-atrophic gastritis' process were mainly enriched in IL-10, IL-4 and IL-13 signaling pathways and antigen presentation pathway. Conclusions: Macrophage, neutrophil and fibroblast are the inflammatory cell phenotypic characteristics of gastritis with cancerous potential, which enriched in IL and antigen presentation pathways.
