A great deal of progress in understanding gene expression has been made using in vitro systems. For most studies, functional assays are carried out using extracts that are prepared in bulk from 10-50 or more liters of cells grown in suspension. However, these large-scale preparations are not amenable to rapidly testing in vitro effects that result from a variety of in vivo cellular treatments or conditions. This journal video article shows a method for preparing functional small-scale nuclear extracts, using HeLa cells as an example. This method is carried out using as few as three 150 mm plates of cells grown as adherent monolayers. To illustrate the efficiency of the small-scale extracts, we show that they are as active as bulk nuclear extracts for coupled RNA Polymerase II transcription/splicing reactions. To demonstrate the utility of the extract protocol, we show that splicing is abolished in extracts prepared from HeLa cells treated with the splicing inhibitor drug E7107. The small-scale protocol should be generally applicable to any process or cell type that can be investigated in vitro using cellular extracts. These include patient cells that are only available in limited quantities or cells exposed to numerous agents such as drugs, DNA damaging agents, RNAi, or transfection, which require the use of small cell populations. In addition, small amounts of freshly grown cells are convenient and/or required for some applications.
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http://dx.doi.org/10.3791/4140 | DOI Listing |
Inflammopharmacology
January 2025
Division of Biochemistry, School of Medical Sciences, University of Phayao, Phayao, 56000, Thailand.
Maejo 341 Sweet potato (MSP) is a new purple sweet potato variety cultivated in Northern Thailand, but its health benefits are unknown. This study aimed to investigate its antioxidant, anti-inflammatory, and anti-osteoporotic activities, as well as its anthocyanin content. The peel and flesh of MSP were extracted with ethanol and water.
View Article and Find Full Text PDFInt J Biol Macromol
January 2025
College of Food and Bioengineering, Qiqihar University, Qiqihar 161006, PR China; Engineering Research Center of Plant Food Processing Technology, Ministry of Education, Qiqihar 161006, PR China. Electronic address:
This study aimed to establish a microwave-assisted method (MAE) for the efficient extraction of polysaccharides from dandelion roots. This study investigated the molecular structure and bioactivity of the polysaccharides from dandelion roots. Extraction conditions were optimized using response surface methodology (RSM).
View Article and Find Full Text PDFBiomed Pharmacother
January 2025
College of Pharmacy and Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul 08826, Republic of Korea; Natural Products Research Institute, Seoul National University, Seoul 08826, Republic of Korea. Electronic address:
A radiopaque hydrogel-in-liposome (RHL) system was developed for micro-computed tomography (μCT) imaging of tumor tissue and simultaneous delivery of a cytotoxic agent. Iopamidol (IPD) and doxorubicin (DOX) were incorporated as the CT contrast and anti-cancer agents, respectively. The presence of a polyethylene glycol hydrogel core in the liposomes was confirmed via attenuated total reflectance Fourier transform infrared, proton nuclear magnetic resonance, and selective solvent extraction.
View Article and Find Full Text PDFFood Addit Contam Part A Chem Anal Control Expo Risk Assess
January 2025
Shanxi Key Laboratory of Food and Drug Safety Prevention and Control, Inspection and Testing Center of Shanxi Province, Taiyuan, Shanxi, China.
Two novel phosphodiesterase 5 (PDE-5) inhibitors were detected in pressed candy using high-performance liquid chromatography (HPLC)-diode array detection. Following extraction with acetonitrile and sonication, the compounds were isolated and purified semi-preparative liquid chromatography. Structural characterisation was achieved through high-resolution mass spectrometry (HRMS) and nuclear magnetic resonance (NMR) spectroscopy.
View Article and Find Full Text PDFInsights Imaging
January 2025
Medical Research Department, Qingdao Hospital, University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital), Qingdao, P. R. China.
Objective: To develop an automatic segmentation model to delineate the adnexal masses and construct a machine learning model to differentiate between low malignant risk and intermediate-high malignant risk of adnexal masses based on ovarian-adnexal reporting and data system (O-RADS).
Methods: A total of 663 ultrasound images of adnexal mass were collected and divided into two sets according to experienced radiologists: a low malignant risk set (n = 446) and an intermediate-high malignant risk set (n = 217). Deep learning segmentation models were trained and selected to automatically segment adnexal masses.
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