52 research outputs found
Anti-Cancer Effect Of A Novel Palladium (II) Complex by Inducing Apoptosis on Ehrlich Ascites Carcinoma in Balb-C Mice
No full textExpression of angiogenesis-related molecules in human leukemic and CB-CD34<sup>+</sup> cells exposed to the vehicle or to high AA.
No full text<p>A) Quantitative real-time PCR (qRT-PCR) analysis of <i>HIF-1α</i> mRNA in CB-CD34<sup>+</sup> and HL60 cells. The cells were treated with vehicle or high AA for 1 h, and then washed, cultured, and analyzed after 24 h. There were no significant differences in the expression levels for the 2 conditions (<i>P</i>>0.05) in CB-CD34<sup>+</sup> cells. In contrast, there were significant differences in the expression levels between the 2 conditions (*<i>P</i><0.0001) in HL60 cells. The values represent the mean ± SD values of triplicate samples. B) Western blotting analysis of HIF-1α in CB-CD34<sup>+</sup> and HL60 cells. The cells were treated with vehicle or high AA for 1 h, and then washed, cultured, and analyzed after 24 h. There were significant differences in the expression levels (*<i>P</i><0.01, **<i>P</i><0.0005). The values are mean ± SD values of triplicate samples. C) Sequential analysis of qRT-PCR results of <i>HIF-1α</i> and <i>VEGF</i> mRNA in HL60 cells. The cells were treated with high AA for 1 h, and then washed, cultured, and analyzed after 1, 3, 22, and 26 h. The expression of <i>VEGF</i> mRNA reduced along with that of <i>HIF-1α</i> over time. Compared with the expression levels at 0 h, there were significant differences in the expression levels (*<i>P</i><0.01, **<i>P</i><0.001, ***<i>P</i><0.0001). The values represent the mean ± SD values of triplicate samples.</p
Integrated Science Teaching in Atmospheric Ice Nucleation Research: Immersion Freezing Experiments
No full textThis paper introduces hands-on curricular modules integrated
with
research in atmospheric ice nucleation, which is an important phenomenon
potentially influencing global climate change. The primary goal of
this work is to promote meaningful laboratory exercises to enhance
the competence of students in the fields of science, technology, engineering,
and math (STEM) by applying an appropriate methodology to laboratory
ice nucleation measurements. To achieve this goal, three laboratory
modules were developed with 18 STEM interns and tested by 28 students
in a classroom setting. Students were trained to experimentally simulate
atmospheric ice nucleation and cloud droplet freezing. For practical
training, this work utilized a simple freezing assay device called
the West Texas Cryogenic Refrigerator Applied to Freezing Test (WT-CRAFT)
system. More specifically, students were provided with hands-on lessons
to calibrate WT-CRAFT with deionized water and apply analytical techniques
to understand the physicochemical properties of bulk water and droplet
freezing. All procedures to implement the developed modules were typewritten
during this process, and shareable read-ahead exploration materials
were developed and compiled as a curricular product. Additionally,
students conducted complementary analyses to identify possible catalysts
of heterogeneous freezing in the water. The water analyses included:
pH, conductivity, surface tension, and electron microscopy–energy-dispersive
X-ray spectroscopy. During the data and image analysis process, students
learned how to analyze droplet freezing spectra as a function of temperature,
screen and interpret the data, perform uncertainty analyses, and estimate
ice nucleation efficiency using computer programs. Based on the formal
program assessment of learning outcomes and direct (yet deidentified)
student feedback, we broadly achieved our goals to (1) improve their
problem-solving skills by combining multidisciplinary science and
math skills and (2) disseminate data and results with variability
and uncertainty. The developed modules can be applied at any institute
to advance undergraduate and graduate curricula in environmental science
The effect of age, days after COVID-19 diagnosis and co-morbidities on the number of TCR clones in a repertoire.
No full text(a) The number of clones/million reads in a repertoire as a function of the patients’ age with Spearman’s Rank Correlation coefficient (ρ) and P value. (b) The number of clones/million reads in a repertoire as a function of the number of days after COVID-19 diagnosis with Spearman’s Rank Correlation coefficient (ρ) and P value. (c) The number of clones/million reads in the repertoires of patients with or without co-morbidities. Significance determined by unpaired Wilcoxon test between each paediatric group, with adjustment for multiple comparisons using Benjamini-Hochberg correction, indicated by: * p (TIF)</p
Escape prevalence in HLA-matched and-mismatched hosts.
No full text<p>Epitopes are labelled where possible with their first three amino acids, and length if necessary to distinguish them. Bars represent 95% binomial confidence limits (Agresti-Coull method). The dotted black line is <i>y</i> = <i>x</i>. Epitopes labelled in bold have a significantly higher proportion of escape in matched hosts than in mismatched hosts (one-tailed Fisher’s Exact test, p < 0.1, note that multiple testing was not corrected for since the purpose of these tests was simply to give a relative measure of significance). Raw data for the number of patients in each category can be found in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004914#pgen.1004914.s016" target="_blank">S3</a> and <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004914#pgen.1004914.s017" target="_blank">S4</a> Tables. First visit (baseline) sequence data was available in at least one gene for 122/125 patients. The range of time from seroconversion among these patients was 1–20 weeks, median 11. (A) At baseline the majority of epitopes have escape at equal prevalence in HLA-matched and-mismatched hosts (B) 52 weeks later within-host evolution has resulted in a higher prevalence of escape in HLA-matched hosts for many epitopes, and in the distribution as a whole HLA-matching and escape are now significantly associated (p < 0.01, permutation test, see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004914#sec004" target="_blank">Methods</a> for details).</p
Kaplan-Meier plots of time to first escape using a midpoint approximation.
No full text<p>Patients who were either missing data for <i>gag</i> or <i>nef</i>, the two genes for which the most data was available, were not included so as not to skew the results due to lack of data. 4 of these patients had no epitopes restricted by their HLA types that were WT at baseline, so <i>n</i> = 61 initially here. (A) Time to first escape in an HLA-restricted epitope (solid line) is plotted along with the 95% confidence intervals (dotted lines). (B) Patients are split according to whether they have one of the more ‘protective’ HLA alleles or not. The set of beneficial alleles was taken to be B*58, B*27, B*57, A*26, B*51, A*11, B*14, B*18, B*08 (all the HLA-A and-B alleles down to B*08 that are present in our data, taken from the ranking in [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004914#pgen.1004914.ref047" target="_blank">47</a>]) as this split the patients approximately in half. Having a protective HLA resulted in a significantly increased risk of HLA-matched escape (p = 0.01, Likelihood Ratio test on Cox Proportional Hazards model with single predictor. Hazard ratio = 3.7, 95% C.I. = (1.2, 11.3)). In both plots the x-axis represents the time since cessation of treatment, or baseline for those not receiving treatment, and vertical checks mark time points at which patients were censored (either because they began long term ART or because there was no further sequence data available for them). Numbers indicate the number of patients who have not yet escaped or been censored at the corresponding time points marked by red dots (0, 27, 55, 93 wks).</p
Cohort characteristics of SARS-CoV-2 infected children and unexposed children.
No full textCohort characteristics of SARS-CoV-2 infected children and unexposed children.</p
Distance to MIRA analysis.
No full text(a) Overview of distance to MIRA analysis: A distance matrix was constructed between all clones in a repertoire and those that mapped to the Adaptive MIRA database, and the distance to the closest MIRA clone was identified. (b) Distance to class I MIRA distribution of TRBV11-2 clones in the repertoires of children with mild COVID-19 or MIS-C. (c) Distance to class II MIRA distribution of TRBV11-2 clones in the repertoires of children with mild COVID-19 or MIS-C.</p
Magnetic Resonance Imaging of Very Small Disruptions of Blood Vessel Permeability in Hypercholesterolemia Mice Using Nitroxide Probes
No full text第5回分子イメージング学会conference objec
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