RESUMEN
RATIONALE: The profiling of natural urinary peptides is a valuable indicator of kidney condition. While front-end separation limits the speed of peptidomic profiling, MS1-based results suffer from limited peptide coverage and specificity. Clinical studies on chronic kidney disease require an effective strategy to balance the trade-off between identification depth and throughput. METHODS: CKD273, a urinary proteome classifier associated with chronic kidney disease, in samples from diabetic nephropathy patients was profiled in parallel using capillary electrophoresis-mass spectrometry (CE-MS), liquid chromatography with mass spectrometry (LC-MS), and matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS). Through cross-comparison of results from MS1 of unfractionated peptides and elution-time-resolved MS1 as well as MS/MS in LC- and CE-MS approaches, we evaluated the contribution of false-positive identification to MS1-based identification and quantitation, and analyzed the benefit of front-end separation in terms of accuracy and efficiency. RESULTS: In LC- and CE-MS, although MS1 data resulted in higher number of identifications than MS/MS, elution-time-dependent analysis revealed extensive interference by non-CKD273 peptides, which would contribute up to 50% to quantitation if they are not separated from genuine CKD273 peptides. In the absence of separation, MS1 data resulted in lower numbers of identifications and abundance pattern that significantly deviated from those by liquid chromatography with tandem mass spectrometry (LC-MS/MS) or capillary electrophoresis with tandem mass spectrometry (CE-MS/MS). CE showed higher identification efficiency even when less sample was used or achieved faster separation. CONCLUSIONS: To ensure the reliability of MS1-based urinary peptide profiling, front-end separation should not be omitted, and elution time should be used in addition to intact mass for identification. Including MS/MS in data acquisition does not compromise the speed or identification number, while benefiting data reliability by providing real-time sequence verification.
RESUMEN
BACKGROUND: Virtual reality becomes popular in laparoscopic surgery especially in the training process. An assessment on the learning curve of virtual reality compared to other methods of training or no training needed to be carried out. MATERIALS AND METHODS: A systematic literature search between 2000 and 2020 was performed through PubMed, Cochrane library's Central, Embase, Clinicaltrials.gov, and Web of Science. All randomized controlled studies included kept the consistency of participants at the baseline and set the same time or repetitions of training. This systematic review and meta-analysis was under the guidance of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Assessing the methodological quality of systematic reviews(AMSTAR). RESULTS: Twenty-three randomized controlled studies and five non-randomized concurrent controlled studies were included among 2692 searched studies. Virtual reality was recommended to be applied among no experience medical students or novice surgeons in the laparoscopic training. It had steeper learning curve compared to no training and traditional trainers. While there was no significant difference between virtual reality and box training or video training in the aspect of learning curve. Moreover, it seemed effective to improve the initial stage of learning curve in actual surgery. CONCLUSION: Virtual reality was not the first choice to be applied into laparoscopic training and it had its applicable surgeons or medical students. The superiority of virtual reality in the skill transfer from training room into operating room needed to be confirmed and complemented with further analyses. More importantly, the cost-effectiveness of virtual reality in the training process and patient safety were badly in need of discussion.
