| 1. |
- Beal, Jacob, et al.
(author)
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Robust estimation of bacterial cell count from optical density
- 2020
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In: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
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Journal article (peer-reviewed)abstract
- Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.
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| 3. |
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- 2019
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Journal article (peer-reviewed)
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| 4. |
- Klionsky, Daniel J., et al.
(author)
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Guidelines for the use and interpretation of assays for monitoring autophagy
- 2012
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In: Autophagy. - : Informa UK Limited. - 1554-8635 .- 1554-8627. ; 8:4, s. 445-544
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Research review (peer-reviewed)abstract
- In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
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| 5. |
- Ye, Chen-Qing, et al.
(author)
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EIS analysis on chloride-induced corrosion behavior of reinforcement steel in simulated carbonated concrete pore solutions
- 2013
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In: Journal of Electroanalytical Chemistry. - : Elsevier BV. - 1572-6657. ; 688, s. 275-281
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Journal article (peer-reviewed)abstract
- The corrosion behavior of reinforcement steel in simulated carbonated concrete pore (SCCP) solution containing different concentrations of chloride was studied by electrochemical impedance spectroscopy (EIS) and linear polarization resistance (LPR) measurements simultaneously, and the topographies of the steel specimens and the elemental distribution at corrosion area were examined by scanning electron microscope (SEM)/electron microprobe analysis (EMPA). The results showed the capacitive loop and polarization resistance decreased with chloride increasing. Furthermore, when the chloride concentration reached a critical value, the Bode plots obviously exhibited two phase angle peaks indicating two time constants. However, when the chloride content exceeded a critical value, the phase angle peaks decreased to one phenomenal peak. An equivalent circuit with two RC loops was used to characterize the corrosion behavior of reinforcement steel in SCCP solution according to the measurements of EIS. Based on the dependence of the equivalent circuit elements on chloride content and immersion time, the formation, growth and breakdown of passive film of the steel were discussed. It was found that the EIS evaluation of corrosion behavior for reinforcement steel in SCCP solution was good agreement with the LPR and SEM measurements. The EMPA mapping revealed MnS inclusions at steel surface play a leading role in the initiation of pitting corrosion.
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| 8. |
- Cai, Qing, et al.
(author)
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Enhanced expression of VEGF-A in β cells increases endothelial cell number but impairs islet morphogenesis and β cell proliferation.
- 2012
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In: Developmental Biology. - : Elsevier BV. - 0012-1606 .- 1095-564X. ; 367:1, s. 40-54
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Journal article (peer-reviewed)abstract
- There is a reciprocal interaction between pancreatic islet cells and vascular endothelial cells (EC) in which EC-derived signals promote islet cell differentiation and islet development while islet cell-derived angiogenic factors promote EC recruitment and extensive islet vascularization. To examine the role of angiogenic factors in the coordinated development of islets and their associated vessels, we used a "tet-on" inducible system (mice expressing rat insulin promoter-reverse tetracycline activator transgene and a tet-operon-angiogenic factor transgene) to increase the β cell production of vascular endothelial growth factor-A (VEGF-A), angiopoietin-1 (Ang1), or angiopoietin-2 (Ang2) during islet cell differentiation and islet development. In VEGF-A overexpressing embryos, ECs began to accumulate around epithelial tubes residing in the central region of the developing pancreas (associated with endocrine cells) as early as embryonic day 12.5 (E12.5) and increased dramatically by E16.5. While α and β cells formed islet cell clusters in control embryos at E16.5, the increased EC population perturbed endocrine cell differentiation and islet cell clustering in VEGF-A overexpressing embryos. With continued overexpression of VEGF-A, α and β cells became scattered, remained adjacent to ductal structures, and never coalesced into islets, resulting in a reduction in β cell proliferation and β cell mass at postnatal day 1. A similar impact on islet morphology was observed when VEGF-A was overexpressed in β cells during the postnatal period. In contrast, increased expression of Ang1 or Ang2 in β cells in developing or adult islets did not alter islet differentiation, development, or morphology, but altered islet EC ultrastructure. These data indicate that (1) increased EC number does not promote, but actually impairs β cell proliferation and islet formation; (2) the level of VEGF-A production by islet endocrine cells is critical for islet vascularization during development and postnatally; (3) angiopoietin-Tie2 signaling in endothelial cells does not have a crucial role in the development or maintenance of islet vascularization.
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| 9. |
- Chang, Ting-Chia, et al.
(author)
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Investigation of somatic single nucleotide variations in human endogenous retrovirus elements and their potential association with cancer
- 2019
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In: PLOS ONE. - : PUBLIC LIBRARY SCIENCE. - 1932-6203. ; 14:4
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Journal article (peer-reviewed)abstract
- Human endogenous retroviruses (HERVs) have been investigated for potential links with human cancer. However, the distribution of somatic nucleotide variations in HERV elements has not been explored in detail. This study aims to identify HERV elements with an over-representation of somatic mutations (hot spots) in cancer patients. Four HERV elements with mutation hotspots were identified that overlap with exons of four human protein coding genes. These hotspots were identified based on the significant over-representation (p<8.62e-4) of non-synonymous single-nucleotide variations (nsSNVs). These genes are TNN (HERV-9/LTR12), OR4K15 (HERV-IP10F/LTR10F), ZNF99 (HERV-W/HERV17/LTR17), and KIR2DL1 (MST/MaLR). In an effort to identify mutations that effect survival, all nsSNVs were further evaluated and it was found that kidney cancer patients with mutation C2270G in ZNF99 have a significantly lower survival rate (hazard ratio = 2.6) compared to those without it. Among HERV elements in the human non-protein coding regions, we found 788 HERVs with significantly elevated numbers of somatic single-nucleotide variations (SNVs) (p<1.60e-5). From this category the top three HERV elements with significantly over-represented SNVs are HERV-H/LTR7, HERV-9/LTR12 and HERV-L/MLT2. Majority of the SNVs in these 788 HERV elements are located in three DNA functional groups: long non-coding RNAs (lncRNAs) (60%), introns (22.2%) and transcriptional factor binding sites (TFBS) (14.8%). This study provides a list of mutational hotspots in HERVs, which could potentially be used as biomarkers and therapeutic targets.
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| 10. |
- Delahanty, Linda M, et al.
(author)
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Effects of Weight Loss, Weight Cycling, and Weight Loss Maintenance on Diabetes Incidence and Change in Cardiometabolic Traits in the Diabetes Prevention Program.
- 2014
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In: Diabetes Care. - : American Diabetes Association. - 1935-5548 .- 0149-5992. ; 37:10, s. 2738-2745
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Journal article (peer-reviewed)abstract
- This study examined specific measures of weight loss in relation to incident diabetes and improvement in cardiometabolic risk factors.RESEARCH DESIGN AND METHODS: This prospective, observational study analyzed nine weight measures, characterizing baseline weight, short- versus long-term weight loss, short- versus long-term weight regain, and weight cycling, within the Diabetes Prevention Program (DPP) lifestyle intervention arm (n = 1,000) for predictors of incident diabetes and improvement in cardiometabolic risk factors over 2 years.RESULTS: Although weight loss in the first 6 months was protective of diabetes (hazard ratio [HR] 0.94 per kg, 95% CI 0.90, 0.98; P < 0.01) and cardiometabolic risk factors (P < 0.01), weight loss from 0 to 2 years was the strongest predictor of reduced diabetes incidence (HR 0.90 per kg, 95% CI 0.87, 0.93; P < 0.01) and cardiometabolic risk factor improvement (e.g., fasting glucose: β = -0.57 mg/dL per kg, 95% CI -0.66, -0.48; P < 0.01). Weight cycling (defined as number of 5-lb [2.25-kg] weight cycles) ranged 0-6 times per participant and was positively associated with incident diabetes (HR 1.33, 95% CI 1.12, 1.58; P < 0.01), fasting glucose (β = 0.91 mg/dL per cycle; P = 0.02), HOMA-IR (β = 0.25 units per cycle; P = 0.04), and systolic blood pressure (β = 0.94 mmHg per cycle; P = 0.01). After adjustment for baseline weight, the effect of weight cycling remained statistically significant for diabetes risk (HR 1.22, 95% CI 1.02, 1.47; P = 0.03) but not for cardiometabolic traits.CONCLUSIONS: Two-year weight loss was the strongest predictor of reduced diabetes risk and improvements in cardiometabolic traits.
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