The water-in-oil emulsion transfer method was developed for preparing giant unilamellar vesicles (GUVs) and is useful for studying cellular functions under conditions that mimic cellular environments. A shortcoming of this method for encapsulating biochemical reactions is that it requires high sugar concentrations to enable the density effect to transverse the oil-water interface. In this study, we investigated the effects of sugars on GUV preparation and several biochemical reactions. We found that changing the sugar in the inner solution from sucrose to maltose or trehalose improved GUV formation. The fusion ratio of the freeze-thaw method was better in the traditional glucose-sucrose condition compared with the other examined conditions. For the inner biochemical reaction, we performed PCR in liposomes. The presence of maltose in the inner solution improved the stability of GUVs against damage caused by thermal cycles. Finally, fructose in the outer solution reduced leakage of the inner solution via pores on the membranes of GUVs. Our findings provide new insight for optimizing sugar conditions for preparing GUVs and inner GUV reactions. This could increase the utilization of GUVs as artificial cell compartment models.
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http://dx.doi.org/10.1021/acs.langmuir.2c00989 | DOI Listing |
Fundam Res
November 2024
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA.
Mitigating methane (CH) emissions from China's coal mines as the largest contributor to anthropogenic CH emissions is vital for limiting global warming. However, the knowledge about CH mitigation potentials and economic costs of Chinese coal mines remain poorly understood, which hinders the formulation of tailored CH mitigation strategies. Here, we estimate and project China's provincial coal mine methane (CMM) emissions, mitigation potentials and costs under various coal production scenarios, by integrating the dynamic emission factors of CMM and key abatement technologies.
View Article and Find Full Text PDFEnviron Pollut
December 2024
Key Laboratory of Arable Land Conservation (Middle and Lower Reaches of Yangtse River), Ministry of Agriculture and Rural affairs, College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China; Hubei Key Laboratory of Soil Environment and Pollution Remediation, College of Resources and Environment, Wuhan 430070, China. Electronic address:
Organoarsenicals are toxic pollutants of global concern, and their environmental geochemical behavior might be greatly controlled by iron (Fe) (hydr)oxides through coprecipitation, which is rarely investigated. Here, the effects of the incorporation of dimethylarsenate (DMAs(V)), a typical organoarsenical, into the ferrihydrite (Fh) structure on the mineral physicochemical properties and Fe(II)-induced phase transformation of DMAs(V)-Fh coprecipitates with As/Fe molar ratios up to 0.0876±0.
View Article and Find Full Text PDFBiosens Bioelectron
December 2024
Department of Life Sciences, Università Degli Studi di Modena e Reggio Emilia, Via Campi 103, Modena, 41125, Italy; Center for Translational Neurophysiology of Speech and Communication, Istituto Italiano di Tecnologia (CTNSC), Via Fossato di Mortara 17-19, Ferrara, 44121, Italy.
According to the Food and Agriculture Organization of the United Nations (FAO) more than 14% of the world's food production is lost every year before reaching retail, and another 17% is lost during the retail stage. The use of the expiration date as the main estimator of the life-end of food products creates unjustified food waste. Sensors capable of quantifying the effective food freshness and quality could substantially reduce food waste and enable more effective management of the food chain.
View Article and Find Full Text PDFJ Food Sci
December 2024
College of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot, China.
As consumers increasingly prioritize food safety and nutritional value, the dairy industry faces a pressing need for rapid and accurate methods to detect essential nutritional components in milk, such as fat, protein, and lactose. Hyperspectral imaging (HSI) technology, known for its non-destructive, fast, and precise nature, shows great promise in food quality assessment. However, the high dimensionality of HSI data poses challenges for effective band selection and model optimization.
View Article and Find Full Text PDFSci Rep
December 2024
College of Computer and Information Engineering, Inner Mongolia Agricultural University, Huhhot, 010000, Inner Mongolia, China.
Mongolian patterns are easily damaged by various factors in the process of inheritance and preservation, and the traditional manual restoration methods are time-consuming, laborious, and costly. With the development of deep learning technology and the rapid growth of the image restoration field, the existing image restoration methods are mostly aimed at natural scene images. They do not apply to Mongolian patterns with complex line texture structures and high saturation-rich colors.
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