4 research outputs found
Weather_Observations_Stellenbosch_University_Library_V5
No full textThis is a dataset related to a fictious research project used for demonstation purposes only. </p
ABCG1 does not co-fractionate with insulin granules and its distribution is closely approximated by GFP-ABCG1.
No full text(A) Fractionation of postnuclear supernatant from INS1 cells by centrifugation on a continuous sucrose density gradient showing the broad distribution of ABCG1 but only modest overlap with higher density granule-containing fractions (10–13). Marker distributions were quantified from western blots and are expressed as fraction of total detected on the gradients. Markers used are proinsulin (ER, TGN and immature granules), carboxypeptidase E (CPE; TGN, immature and mature granules), and syntaxin 6 (TGN and endosomes). Full-size western blots are shown in Figure A in S1 Fig. (B) Fractionation of postnuclear supernatant from MIN6 cells confirming both the broad distribution of ABCG1, appreciable overlap with proinsulin-containing fractions (as reported previously [17]), and limited distribution in mature granules identified by insulin ELISA. Markers are as in (A). For both INS1 (A) and MIN6 (B) cells, two independent experiments were performed with the same outcomes; the data presented are from one experiment in each case. (C) Western blot using anti-ABCG1 showing the stable expression in INS1 cells of GFP-ABCG1 fusion protein (GFP-G1) at ~2.5-fold above the level of endogenous ABCG1. (D) Mixing experiment as analyzed by continuous sucrose gradient centrifugation of postnuclear supernatant fractions. Data are presented as fraction of total detected from western blots. Sample blots shown below the first two panels. Panel 1. GFP-G1 and endogenous ABCG1 distributions for cells stably expressing GFP-G1. Panel 2. Distributions observed for a mixed postnuclear supernatant containing 1 part GFP-G1 expressing cells and 5 parts non-transfected INS1 cells highlighting the very similar distributions of endogenous ABCG1 deriving mostly from the non-transfected cells and GFP-G1 from the transfected cells. Panel 3. Replots of endogenous ABCG1 distribution from panel 1 (Unmixed GFP-G1) and endogenous ABCG1 from panel 2 (Mixed PNS) illustrating that expression of GFP-G1 minimally alters the distribution of endogenous ABCG1. Panel 4. Replots of GFP-G1 distribution from panels 1 and 2 used as an index of reproducibility of the two gradients. Data presented are from one of two experiments with the same outcome. As for (A), full-size western blots for (B-D) are shown in Figures B-D of S1 Fig.</p
Методичні вказівки до проведення практичних занять і виконання розрахунково-графічної роботи з дисципліни «Інформаційні системи і технології» (для студентів 2 курсу денної форми навчання освітньо-кваліфікаційного рівня бакалавр, напряму підготовки 6.070101 - “ Транспортні технології (за видами транспорту)”).
No full textThe State of Open Data 2022
No full textWe're proud to release our seventh State of Open Data report.
Based on a global survey, the report is now in its seventh year and provides insights into researchers’ attitudes towards and experiences of open data. With more than 5,400 respondents, the 2022 survey is the largest since the COVID-19 pandemic began.
This year’s report also includes guest articles from open data experts at the National Institutes of Health (NIH), the White House Office of Science and Technology Policy (OSTP), the Computer Network Information Center, Chinese Academy of Sciences (CNIC, CAS), publishers and universities.
Version 5 includes link to full survey results and questionnaire with updated links, corrected author affiliation on the contents page and throughout. </p
