Circulating tumor cells (CTCs) have been recognized as a general biomarker for the early detection, diagnosis and therapy monitoring of cancer. Due to their extreme rarity in peripheral blood, the isolation and analysis of CTCs with high efficiency, high purity and high viability remains a tremendous technological challenge. Herein, we combined tetrahedral DNA framework (TDFs), herringbone channel (HB) chip, together with aptamer-triggered hybridization chain reaction (apt-HCR) to develop an efficient microfluidic system (T-μFS) for capture and release of simulated CTCs. The capture efficiency of MCF-7 cells was from 83.3% to 94.2% when the cell numbers ranged from 10 to 10 using our T-μFS in the whole blood. The release efficiency of the MCF-7 cells was 96.2% and the MCF-7 cell viability after release was 94.6% using our T-μFS in PBS buffer. Reculture and RT-qPCR studies showed that there was almost no damage by the capture and release treatment for the MCF-7 cells viability. These results revealed that our T-μFS could be developed as an integrated and automatic technical platform with great performance for multivalent capture and release of CTCs and have a wide application prospect for tumor liquid biopsy.
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http://dx.doi.org/10.1016/j.mtbio.2022.100346 | DOI Listing |
BMJ Open
January 2025
Centre for Neuroscience Studies, Queen's University, Kingston, Ontario, Canada.
Introduction: Survivors of critical illness and their caregivers are at risk for long-term cognitive, physical and psychiatric impairments known as post-intensive care syndrome (PICS) and PICS-family, respectively. This study will assess the feasibility of a randomised controlled trial (RCT) evaluating an intensive care unit (ICU) follow-up care bundle versus standard-of-care for ICU patients and their caregivers.
Methods And Analysis: This is a single-centre feasibility study.
Bioorg Chem
December 2024
Department of Chemistry, University of Richmond, Gottwald Science Center, B-100 138 UR Drive, Richmond, VA 23173, United States. Electronic address:
We report the development of a new electron-rich aniline (ERA)-based cleavable linker. Anilines can be incorporated into peptides during SPPS and are stable to most reaction conditions. ERA-containing peptides can be cleaved rapidly in the presence of oxidants, such as DDQ, CAN, and NaIO, in 30 min at room temperature.
View Article and Find Full Text PDFPLoS One
January 2025
University of Miami Rosenstiel School of Marine, Atmospheric, and Earth Science, Miami, Florida, United States of America.
Nurse sharks (Ginglymostoma cirratum), especially juveniles, are often encountered by near-shore and shore-based recreational anglers and are suggested to exhibit minimal behavioral and physiological responses to capture, largely based on studies of adults using commercial or scientific fishing methods. To quantify the sub-lethal effects of recreational angling on juvenile nurse sharks, 27 individuals (across 31 angling events) were caught using hook-and-line fishing methods. Over a 30-min period, 4 blood samples were taken with variable time intervals between sampling (i.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States of America.
Transitional care management (TCM) visits have been shown to reduce 30-day readmissions, but it is unclear whether the decrease arises from the TCM visit itself or from clinic-level changes to meet the requirements of the TCM visits. We conducted a cross-sectional analysis using data from Northwell Health to examine the association between the type of post-discharge follow-up visits (TCM visits versus non-TCM visits based on billing) and 30-day readmission. Furthermore, we assessed whether being seen by a provider who frequently utilizes TCM visits or the TCM visit itself was associated with 30-day readmission.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Department of Computer Science, Hunan University, Changsha 410008, China.
Recently, the impressive performance of large language models (LLMs) on a wide range of tasks has attracted an increasing number of attempts to apply LLMs in drug discovery. However, molecule optimization, a critical task in the drug discovery pipeline, is currently an area that has seen little involvement from LLMs. Most of existing approaches focus solely on capturing the underlying patterns in chemical structures provided by the data, without taking advantage of expert feedback.
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