Purpose: To assess the performance of full dose (FD) positron emission tomography (PET) image synthesis in both image and projection space from low-dose (LD) PET images/sinograms without sacrificing diagnostic quality using deep learning techniques. Methods: Clinical brain PET/CT studies of 140 patients were retrospectively employed for LD to FD PET conversion. 5% of the events were randomly selected from the FD list-mode PET data to simulate a realistic LD acquisition. A modified 3D U-Net model was implemented to predict FD sinograms in the projection-space (PSS) and FD images in image-space (PIS) from their corresponding LD sinograms/images, respectively. The quality of the predicted PET images was assessed by two nuclear medicine specialists using a five-point grading scheme. Quantitative analysis using established metrics including the peak signal-to-noise ratio (PSNR), structural similarity index metric (SSIM), region-wise standardized uptake value (SUV) bias, as well as first-, second- and high-order texture radiomic features in 83 brain regions for the test and evaluation dataset was also performed. Results: All PSS images were scored 4 or higher (good to excellent) by the nuclear medicine specialists. PSNR and SSIM values of 0.96 ± 0.03, 0.97 ± 0.02 and 31.70 ± 0.75, 37.30 ± 0.71 were obtained for PIS and PSS, respectively. The average SUV bias calculated over all brain regions was 0.24 ± 0.96% and 1.05 ± 1.44% for PSS and PIS, respectively. The Bland-Altman plots reported the lowest SUV bias (0.02) and variance (95% CI: -0.92, +0.84) for PSS compared with the reference FD images. The relative error of the homogeneity radiomic feature belonging to the Grey Level Co-occurrence Matrix category was -1.07 ± 1.77 and 0.28 ± 1.4 for PIS and PSS, respectively Conclusion: The qualitative assessment and quantitative analysis demonstrated that the FD PET prediction in projection space led to superior performance, resulting in higher image quality and lower SUV bias and variance compared to FD PET prediction in the image domain.

Recently introduced PET systems using silicon photomultipliers with digital readout (dPET) have an improved timing and spatial resolution, aiming at a better image quality, over conventional PET (cPET) systems. We prospectively evaluated the performance of a dPET system in patients with cancer, as compared to high-resolution (HR) cPET imaging. Methods: After a single FDG-injection, 66 patients underwent dPET (Vereos, Philips Healthcare) and cPET (Ingenuity TF, Philips Healthcare) imaging in a randomized order. We used HR-reconstructions (2x2x2 mm³ voxels) for both scanners and determined SUV_max, SUVmean, lesion-to-background ratio (LBR), metabolic tumor volume (MTV) and lesion diameter in up to 5 FDG-positive lesions per patient. Furthermore, we counted the number of visible and measurable lesions on each PET scan. Two nuclear medicine specialists blindly determined the Tumor Node Metastasis (TNM) score from both image sets in 30 patients referred for initial staging. For all 66 patients, these specialists separately and blindly evaluated image quality (4-point scale) and determined the scan preference. Results: We included 238 lesions that were visible and measurable on both PET scans. We found 37 additional lesions on dPET in 27 patients (41%), which were unmeasurable (n = 14) or invisible (n = 23) on cPET. SUVmean, SUV_max, LBR and MTV on cPET were 5.2±3.9 (mean±SD), 6.9±5.6, 5.0±3.6 and 2991±13251 mm³, respectively. On dPET SUVmean, SUV_max and LBR increased 24%, 23% and 27%, respectively (p<0.001) while MTV decreased 13% (p<0.001) compared to cPET. Visual analysis showed TNM upstaging with dPET in 13% of the patients (4/30). dPET images also scored higher in image quality (P = 0.003) and were visually preferred in the majority of cases (65%). Conclusion: Digital PET improved the detection of small lesions, upstaged the disease and images were visually preferred as compared to high-resolution conventional PET. More studies are necessary to confirm the superior diagnostic performance of digital PET.

Latest digital whole-body PET scanners provide a combination of higher sensitivity and improved spatial and timing resolution. We performed a lesion detectability study on two generations of Siemens Biograph PET/CT scanners, the mCT and Vision, to study the impact of improved physical performance on clinical performance. Our hypothesis is that the improved performance of the Vision will result in improved lesion detectability, allowing shorter imaging times or equivalently, lower injected dose. Methods: Data were acquired with the Society of Nuclear Medicine and Molecular Imaging Clinical Trials Network torso phantom combined with a 20-cm diameter cylindrical phantom. Spherical lesions were emulated by acquiring spheres-in-air data, and combining it with the phantom data to generate combined datasets with embedded lesions of known contrast. Two sphere sizes and uptakes were used: 9.89 mm diameter spheres with 6:1 (lung) and 3:1 (cylinder) and 4.95 mm diameter spheres with 9.6:1 (lung) and 4.5:1 (cylinder) local activity concentration uptakes. Standard image reconstruction was performed: ordinary Poisson ordered subsets expectation maximization algorithm with point spread function and time-of-flight modeling and post-reconstruction smoothing with a 5 mm Gaussian filter. The Vision images were also generated without any post-reconstruction smoothing. Generalized scan statistics methodology was used to estimate the area under the localization receiver operating characteristic curve (ALROC). Results: Higher sensitivity and improved TOF performance of Vision leads to reduced contrast in the background noise nodule distribution. Measured lesion contrast is also higher on the Vision due to its improved spatial resolution. Hence, the ALROC values are noticeably higher for the Vision relative to the mCT. Conclusion: Improved overall performance of the Vision provides a factor of 4-6 reduction in imaging time (or injected dose) over the mCT when using the ALROC metric for lesions >9.89 mm in diameter. Smaller lesions are barely detected in the mCT, leading to even higher ALROC gains with the Vision. Improved spatial resolution of the Vision also leads to a higher measured contrast that is closer to the real uptake, implying improved quantification. Post-reconstruction smoothing, however, reduces this improvement in measured contrast, thereby reducing the ALROC values for small, high uptake lesions.

A data-driven method for respiratory gating in PET has recently been commercially developed. We sought to compare the performance of the algorithm to an external, device-based system for oncological [¹⁸F]-FDG PET/CT imaging. Methods: 144 whole-body [¹⁸F]-FDG PET/CT examinations were acquired using a Discovery D690 or D710 PET/CT scanner (GE Healthcare), with a respiratory gating waveform recorded by an external, device based respiratory gating system. In each examination, two of the bed positions covering the liver and lung bases were acquired with duration of 6 minutes. Quiescent period gating retaining ~50% of coincidences was then able to produce images with an effective duration of 3 minutes for these two bed positions, matching the other bed positions. For each exam, 4 reconstructions were performed and compared: data driven gating (DDG-retro), external device-based gating (RPM Gated), no gating but using only the first 3 minutes of data (Ungated Matched), and no gating retaining all coincidences (Ungated Full). Lesions in the images were quantified and image quality was scored by a radiologist, blinded to the method of data processing. Results: The use of DDG-retro was found to increase SUVmax and to decrease the threshold-defined lesion volume in comparison to each of the other reconstruction options. Compared to RPM-gated, DDG-retro gave an average increase in SUV_max of 0.66 ± 0.1 g/mL (n=87, p<0.0005). Although results from the blinded image evaluation were most commonly equivalent, DDG-retro was preferred over RPM gated in 13% of exams while the opposite occurred in just 2% of exams. This was a significant preference for DDG-retro (p=0.008, n=121). Liver lesions were identified in 23 exams. Considering this subset of data, DDG-retro was ranked superior to Ungated Full in 6/23 (26%) of cases. Gated reconstruction using the external device failed in 16% of exams, while DDG-retro always provided a clinically acceptable image. Conclusion: In this clinical evaluation, the data driven respiratory gating technique provided superior performance as compared to the external device-based system. For the majority of exams the performance was equivalent, but data driven respiratory gating had superior performance in 13% of exams, leading to a significant preference overall.

The purpose of this study was to establish the dose-response relationship of selective internal radiation therapy (SIRT) in patients with metastatic colorectal cancer (mCRC), when informed by radiobiological sensitivity parameters derived from mCRC cell lines exposed to yttrium-90 (⁹⁰Y). Methods: 23 mCRC patients with liver metastases refractory to chemotherapy were included. ⁹⁰Y bremsstrahlung SPECT images were transformed into dose maps assuming the local dose deposition method. Baseline and follow-up CT scans were segmented to derive liver and tumor volumes. Mean, median, and D₇₀ (minimum dose to 70% of tumor volume) values determined from dose maps were correlated with change in tumor volume and vRECIST response using linear and logistic regression, respectively. Radiosensitivity parameters determined by clonogenic assays of mCRC cell lines HT-29 and DLD-1 after exposure to ⁹⁰Y or external beam radiotherapy (EBRT; 6MV photons) were used in biological effective dose (BED) calculations. Results: Mean administered radioactivity was 1469±428 MBq (847-2185 MBq), achieving a mean radiation absorbed tumor dose of 35.5±9.4 Gy and mean normal liver dose of 26.4±6.8 Gy. A 1.0 Gy increase in mean, median, and D₇₀ absorbed dose was associated with reduction in tumor volume of 1.8%, 1.8%, and 1.5%, respectively, and increased probability of vRECIST response (odds ratio: 1.09, 1.09, and 1.10 respectively). Threshold mean, median and D₇₀ doses for response were 48.3, 48.8, and 41.8 Gy respectively. EBRT-equivalent BEDs for ⁹⁰Y are up to 50% smaller than those calculated by applying protraction-corrected radiobiological parameters derived from EBRT alone. Conclusion: Dosimetric studies have assumed equivalence between ⁹⁰Y SIRT and EBRT, leading to inflation of BED for SIRT and possible under-treatment. Radiobiological parameters for ⁹⁰Y were applied to a BED model, providing a calculation method that has the potential to improve assessment of tumor control.

Invitation Only Research Event

Event participants

Professor Nick Binedell, Founding Director and Sasol Chair of Strategic Management, Gordon Institute of Business Science (GIBS), University of Pretoria

Research Event

Event participants

Hon. Manuel José Nunes Júnior, Minister of State for Economic Coordination, Republic of Angola
Chair: Dr Alex Vines OBE, Managing Director, Ethics, Risk & Resilience; Director, Africa Programme, Chatham House

Research Event

Event participants

Tutu Alicante, Executive Director, EG Justice
Chair: Dr Alex Vines OBE, Managing Director, Ethics, Risk & Resilience; Director, Africa Programme, Chatham House

Research Event

Event participants

Paul Mashatile, Treasurer General, African National Congress (ANC)

In bottom-up, label-free discovery proteomics, biological samples are acquired in a data-dependent (DDA) or data-independent (DIA) manner, with peptide signals recorded in an intact (MS1) and fragmented (MS2) form. While DDA has only the MS1 space for quantification, DIA contains both MS1 and MS2 at high quantitative quality. DIA profiles of complex biological matrices such as tissues or cells can contain quantitative interferences, and the interferences at the MS1 and the MS2 signals are often independent. When comparing biological conditions, the interferences can compromise the detection of differential peptide or protein abundance and lead to false positive or false negative conclusions.

We hypothesized that the combined use of MS1 and MS2 quantitative signals could improve our ability to detect differentially abundant proteins. Therefore, we developed a statistical procedure incorporating both MS1 and MS2 quantitative information of DIA. We benchmarked the performance of the MS1-MS2-combined method to the individual use of MS1 or MS2 in DIA using four previously published controlled mixtures, as well as in two previously unpublished controlled mixtures. In the majority of the comparisons, the combined method outperformed the individual use of MS1 or MS2. This was particularly true for comparisons with low fold changes, few replicates, and situations where MS1 and MS2 were of similar quality. When applied to a previously unpublished investigation of lung cancer, the MS1-MS2-combined method increased the coverage of known activated pathways.

Since recent technological developments continue to increase the quality of MS1 signals (e.g. using the BoxCar scan mode for Orbitrap instruments), the combination of the MS1 and MS2 information has a high potential for future statistical analysis of DIA data.

Top-down proteomics studies intact proteoform mixtures and offers important advantages over more common bottom-up proteomics technologies, as it avoids the protein inference problem. However, achieving complete molecular characterization of investigated proteoforms using existing technologies remains a fundamental challenge for top-down proteomics. Here, we benchmark the performance of ultraviolet photodissociation (UVPD) using 213 nm photons generated by a solid-state laser applied to the study of intact proteoforms from three organisms. Notably, the described UVPD setup applies multiple laser pulses to induce ion dissociation, and this feature can be used to optimize the fragmentation outcome based on the molecular weight of the analyzed biomolecule. When applied to complex proteoform mixtures in high-throughput top-down proteomics, 213 nm UVPD demonstrated a high degree of complementarity with the most employed fragmentation method in proteomics studies, higher-energy collisional dissociation (HCD). UVPD at 213 nm offered higher average proteoform sequence coverage and degree of proteoform characterization (including localization of post-translational modifications) than HCD. However, previous studies have shown limitations in applying database search strategies developed for HCD fragmentation to UVPD spectra which contains up to nine fragment ion types. We therefore performed an analysis of the different UVPD product ion type frequencies. From these data, we developed an ad hoc fragment matching strategy and determined the influence of each possible ion type on search outcomes. By paring down the number of ion types considered in high-throughput UVPD searches from all types down to the four most abundant, we were ultimately able to achieve deeper proteome characterization with UVPD. Lastly, our detailed product ion analysis also revealed UVPD cleavage propensities and determined the presence of a product ion produced specifically by 213 nm photons. All together, these observations could be used to better elucidate UVPD dissociation mechanisms and improve the utility of the technique for proteomic applications.

Lung cancer (LC) remains the leading cause of mortality from malignant tumors worldwide. In our previous study, we surveyed both IgG and IgM-bound serological biomarkers and validated a panel of IgG-bound autoantigens for early LC diagnosis with 50% sensitivity at 90% specificity. To further improve the performance of these serological biomarkers, we surveyed HuProt arrays, comprised of 20,240 human proteins, for IgA-bound autoantigens because IgAs are a major immunoglobulin isotype in the lung. Integrating with IgG-bound autoantigens, we discovered and validated a combined biomarker panel using ELISA-format tests. Specifically, in Phase I, we obtained IgA-based autoimmune profiles of 69 early stage LC patients, 30 healthy subjects and 25 patients with lung benign lesions (LBL) on HuProt arrays and identified 28 proteins as candidate autoantigens that were significantly associated with early stage LC. In Phase II, we re-purified the autoantigens and converted them into an ELISA-format testing to profile an additional large cohort, comprised of 136 early stage LC patients, 58 healthy individuals, and 29 LBL patients. Integration of IgG autoimmune profiles allowed us to identify and validate a biomarker panel of three IgA autoantigens (i.e. BCL7A, and TRIM33 and MTERF4) and three IgG autoantigens (i.e. CTAG1A, DDX4 and MAGEC2) for diagnosis of early stage LC with 73.5% sensitivity at >85% specificity. In Phase III, the performance of this biomarker panel was confirmed with an independent cohort, comprised of 88 early stage LC patients, 18 LBL patients, and 36 healthy subjects. Finally, a blind test on 178 serum samples was conducted to confirm the performance of the biomarker panel. In summary, this study demonstrates for the first time that an integrated panel of IgA/IgG autoantigens can serve as valuable biomarkers to further improve the performance of early diagnosis of LC.

For more than two decades naturally presented, human leukocyte antigen (HLA)-restricted peptides (immunopeptidome) have been eluted and sequenced using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Since, identified disease-associated HLA ligands have been characterized and evaluated as potential active substances. Treatments based on HLA-presented peptides have shown promising results in clinical application as personalized T cell-based immunotherapy. Peptide vaccination cocktails are produced as investigational medicinal products under GMP conditions. To support clinical trials based on HLA-presented tumor-associated antigens, in this study the sensitive LC-MS/MS HLA class I antigen identification pipeline was fully validated for our technical equipment according to the current US Food and Drug Administration (FDA) and European Medicines Agency (EMA) guidelines.

The immunopeptidomes of JY cells with or without spiked-in, isotope labeled peptides, of peripheral blood mononuclear cells of healthy volunteers as well as a chronic lymphocytic leukemia and a bladder cancer sample were reliably identified using a data-dependent acquisition method. As the LC-MS/MS pipeline is used for identification purposes, the validation parameters include accuracy, precision, specificity, limit of detection and robustness.

HNF4α is a nuclear receptor produced as 12 isoforms from two promoters by alternative splicing. To characterize the transcriptional capacities of all 12 HNF4α isoforms, stable lines expressing each isoform were generated. The entire transcriptome associated with each isoform was analyzed as well as their respective interacting proteome. Major differences were noted in the transcriptional function of these isoforms. The α1 and α2 isoforms were the strongest regulators of gene expression whereas the α3 isoform exhibited significantly reduced activity. The α4, α5, and α6 isoforms, which use an alternative first exon, were characterized for the first time, and showed a greatly reduced transcriptional potential with an inability to recognize the consensus response element of HNF4α. Several transcription factors and coregulators were identified as potential specific partners for certain HNF4α isoforms. An analysis integrating the vast amount of omics data enabled the identification of transcriptional regulatory mechanisms specific to certain HNF4α isoforms, hence demonstrating the importance of considering all isoforms given their seemingly diverse functions.

The cellular energy sensor AMP-activated protein kinase (AMPK) is a metabolic regulator that mediates adaptation to nutritional variations to maintain a proper energy balance in cells. We show here that suckling-weaning and fasting-refeeding transitions in rodents are associated with changes in AMPK activation and the cellular energy state in the liver. These nutritional transitions were characterized by a metabolic switch from lipid to glucose utilization, orchestrated by modifications in glucose levels and the glucagon/insulin ratio in the bloodstream. We therefore investigated the respective roles of glucose and pancreatic hormones on AMPK activation in mouse primary hepatocytes. We found that glucose starvation transiently activates AMPK, whereas changes in glucagon and insulin levels had no impact on AMPK. Challenge of hepatocytes with metformin-induced metabolic stress strengthened both AMPK activation and cellular energy depletion under limited-glucose conditions, whereas neither glucagon nor insulin altered AMPK activation. Although both insulin and glucagon induced AMPKα phosphorylation at its Ser485/491 residue, they did not affect its activity. Finally, the decrease in cellular ATP levels in response to an energy stress was additionally exacerbated under fasting conditions and by AMPK deficiency in hepatocytes, revealing metabolic inflexibility and emphasizing the importance of AMPK for maintaining hepatic energy charge. Our results suggest that nutritional changes (i.e. glucose availability), rather than the related hormonal changes (i.e. the glucagon/insulin ratio), sensitize AMPK activation to the energetic stress induced by the dietary transition during fasting. This effect is critical for preserving the cellular energy state in the liver.

The millions of customers, the short deadline: how the public service's digital revolution will start.

Jeroen van Smeden
Apr 7, 2020; 0:jlr.RA120000639v1-jlr.RA120000639
Research Articles

Chelsea DeLeon
May 1, 2020; 61:767-777
Research Articles

Souad Amiar
Apr 15, 2020; 0:jlr.ILR120000753v1-jlr.ILR120000753
Images in Lipid Research

We finally get the IoT acronym the pod has been waiting for as we discuss Bitcoin and 17th century Dutch finance. Charlotte Jee informs Henry Burrell, David Price and Scott Carey.

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Individuals with Netherton syndrome (NTS) have increased serine protease activity, which strongly impacts the barrier function of the skin epidermis and leads to skin inflammation. Here, we investigated how serine protease activity in NTS correlates with changes in the stratum corneum ceramides, which are crucial components of the skin barrier. We examined two key enzymes involved in epidermal ceramide biosynthesis, glucocerebrosidase (GBA) and acid-sphingomyelinase (ASM). We compared in situ expression levels and activities of GBA and ASM between NTS patients and controls and correlated the expression and activities with i) stratum corneum ceramide profiles, ii) in situ serine protease activity, and iii) clinical presentation of patients. Using activity-based probe labeling, we visualized and localized active, epidermal GBA, and a newly developed in situ zymography method enabled us to visualize and localize active ASM. Reduction in active GBA in NTS patients coincided with increased ASM activity, particularly in areas with increased serine protease activity. NTS patients with scaly erythroderma exhibited more pronounced anomalies in GBA and ASM activities than patients with ichthyosis linearis circumflexa. They also displayed a stronger increase in stratum corneum ceramides processed via ASM. We conclude that changes in the localization of active GBA and ASM correlate with i) altered stratum corneum ceramide composition in NTS patients, ii) local serine protease activity, and iii) the clinical manifestation of NTS. 

11 March 2020

25 April 2020

6 May 2020

This article provides an introduction to Fourier transform-based mass spectrometry (FTMS). The key performance characteristics of FTMS, mass accuracy and resolution, are presented in the view of how they impact the interpretation of measurements in proteomic applications. The theory and principles of operation of two types of mass analyzer, Fourier transform ion cyclotron resonance and Orbitrap, are described. Major benefits as well as limitations of FTMS technology are discussed in the context of practical sample analysis, and illustrated with examples included as figures in this text and in the accompanying slide set. Comparisons highlighting the performance differences between the two mass analyzers are made where deemed useful in assisting the user with choosing the most appropriate technology for his/her application. Recent developments of these high-performing mass spectrometers are mentioned to provide a future outlook.

As the capability of mass spectrometry-based proteomics has matured, tens of thousands of peptides can be measured simultaneously, which has the benefit of offering a systems view of protein expression. However, a major challenge is that with an increase in throughput, protein quantification estimation from the native measured peptides has become a computational task. A limitation to existing computationally-driven protein quantification methods is that most ignore protein variation, such as alternate splicing of the RNA transcript and post-translational modifications or other possible proteoforms, which will affect a significant fraction of the proteome. The consequence of this assumption is that statistical inference at the protein level, and consequently downstream analyses, such as network and pathway modeling, have only limited power for biomarker discovery. Here, we describe a Bayesian model (BP-Quant) that uses statistically derived peptides signatures to identify peptides that are outside the dominant pattern, or the existence of multiple over-expressed patterns to improve relative protein abundance estimates. It is a research-driven approach that utilizes the objectives of the experiment, defined in the context of a standard statistical hypothesis, to identify a set of peptides exhibiting similar statistical behavior relating to a protein. This approach infers that changes in relative protein abundance can be used as a surrogate for changes in function, without necessarily taking into account the effect of differential post-translational modifications, processing, or splicing in altering protein function. We verify the approach using a dilution study from mouse plasma samples and demonstrate that BP-Quant achieves similar accuracy as the current state-of-the-art methods at proteoform identification with significantly better specificity. BP-Quant is available as a MatLab ® and R packages at https://github.com/PNNL-Comp-Mass-Spec/BP-Quant.

7 May 2020 , Volume 96, Number 3

27 November 2019

11 March 2020

Invitation Only Research Event

Event participants

Invitation Only Research Event

Bile acids (BAs) serve multiple biological functions, ranging from the absorption of lipids and fat-soluble vitamins to serving as signaling molecules through the direct activation of dedicated cellular receptors. Synthesized by both host and microbial pathways, BAs are increasingly understood as participating in the regulation of numerous pathways relevant to metabolic diseases, including lipid and glucose metabolism, energy expenditure, and inflammation. Quantitative analyses of BAs in biological matrices can be problematic due to their unusual and diverse physicochemical properties, making optimization of a method that shows good accuracy, precision, efficiency of extraction, and minimized matrix effects across structurally distinct human and murine BAs challenging. Herein we develop and clinically validate a stable-isotope-dilution LC/MS/MS method for the quantitative analysis of numerous primary and secondary BAs in both human and mouse biological matrices. We also utilize this tool to investigate gut microbiota participation in the generation of structurally specific BAs in both humans and mice. We examine circulating levels of specific BAs and in a clinical case-control study of age- and gender-matched type 2 diabetes mellitus (T2DM) versus nondiabetics. BAs whose circulating levels are associated with T2DM include numerous 12α-hydroxyl BAs (taurocholic acid, taurodeoxycholic acid, glycodeoxycholic acid, deoxycholic acid, and 3-ketodeoxycholic acid), while taurohyodeoxycholic acid was negatively associated with diabetes. The LC/MS/MS-based platform described should serve as a robust, high-throughput investigative tool for studying the potential involvement of structurally specific BAs and the gut microbiome on both physiological and disease processes.

Pyruvate kinase M2 (PKM2) links metabolic and inflammatory dysfunction in atherosclerotic coronary artery disease; however, its role in oxidized LDL (Ox-LDL)-induced macrophage foam cell formation and inflammation is unknown and therefore was studied. In recombinant mouse granulocyte-macrophage colony-stimulating factor-differentiated murine bone marrow-derived macrophages, early (1–6 h) Ox-LDL treatment induced PKM2 tyrosine 105 phosphorylation and promotes its nuclear localization. PKM2 regulates aerobic glycolysis and inflammation because PKM2 shRNA or Shikonin abrogated Ox-LDL-induced hypoxia-inducible factor-1α target genes lactate dehydrogenase, glucose transporter member 1, interleukin 1β (IL-1β) mRNA expression, lactate, and secretory IL-1β production. PKM2 inhibition significantly increased Ox-LDL-induced ABCA1 and ABCG1 protein expression and NBD-cholesterol efflux to apoA1 and HDL. PKM2 shRNA significantly inhibited Ox-LDL-induced CD36, FASN protein expression, DiI-Ox-LDL binding and uptake, and cellular total cholesterol, free cholesterol, and cholesteryl ester content. Therefore, PKM2 regulates lipid uptake and efflux. DASA-58, a PKM2 activator, downregulated LXR-α, ABCA1, and ABCG1, and augmented FASN and CD36 protein expression. Peritoneal macrophages showed similar results. Ox-LDL induced PKM2- SREBP-1 interaction and FASN expression in a PKM2-dependent manner. Therefore, this study suggests a role for PKM2 in Ox-LDL-induced aerobic glycolysis, inflammation, and macrophage foam cell formation.

Many clinical studies and epidemiological investigations have clearly demonstrated that women are twice as likely to develop cholesterol gallstones as men, and oral contraceptives and other estrogen therapies dramatically increase that risk. Further, animal studies have revealed that estrogen promotes cholesterol gallstone formation through the estrogen receptor (ER) α, but not ERβ, pathway. More importantly, some genetic and pathophysiological studies have found that G protein-coupled estrogen receptor (GPER) 1 is a new gallstone gene, Lith18, on chromosome 5 in mice and produces additional lithogenic actions, working independently of ERα, to markedly increase cholelithogenesis in female mice. Based on computational modeling of GPER, a novel series of GPER-selective antagonists were designed, synthesized, and subsequently assessed for their therapeutic effects via calcium mobilization, cAMP, and ERα and ERβ fluorescence polarization binding assays. From this series of compounds, one new compound, 2-cyclohexyl-4-isopropyl-N-(4-methoxybenzyl)aniline (CIMBA), exhibits superior antagonism and selectivity exclusively for GPER. Furthermore, CIMBA reduces the formation of 17β-estradiol-induced gallstones in a dose-dependent manner in ovariectomized mice fed a lithogenic diet for 8 weeks. At 32 μg/day/kg CIMBA, no gallstones are found, even in ovariectomized ERα (^–/–) mice treated with 6 μg/day 17β-estradiol and fed the lithogenic diet for 8 weeks. In conclusion, CIMBA treatment protects against the formation of estrogen-induced cholesterol gallstones by inhibiting the GPER signaling pathway in female mice. CIMBA may thus be a new agent for effectively treating cholesterol gallstone disease in women.­

If your business key column is a name literal, like " business key "n, a syntax error occurs when that variable name does not follow standard SAS naming conventions.

In SAS Data Integration Studio, the columns that you select to include in the target table in a Business Rules transformation appear in the Selected columns area in a random order. Th

All 30 Major League teams will wear special "MLB 150" patches on their uniforms for the entire 2019 season in honor of the 150th anniversary of the 1869 Cincinnati Red Stockings, the first openly all-salaried professional baseball team.

Objective:

GPR40 is a G protein-coupled receptor regulating free fatty acid-induced insulin secretion. We have generated transgenic mice overexpressing the human GPR40 gene (hGPR40-Tg) under control of the mouse insulin II promoter and have used them to examine the role of GPR40 in the regulation of insulin secretion and glucose homeostasis.

Insulin is first produced in pancreatic β-cells as the precursor prohormone proinsulin. Defective proinsulin processing has been implicated in the pathogenesis of both type 1 and type 2 diabetes. Though there is substantial evidence that mouse β-cells process proinsulin using prohormone convertase 1/3 (PC1/3) then prohormone convertase 2 (PC2), this finding has not been verified in human β-cells. Immunofluorescence with validated antibodies reveals that there was no detectable PC2 immunoreactivity in human β-cells and little PCSK2 mRNA by in situ hybridization. Similarly, rat β-cells were not immunoreactive for PC2. In all histological experiments, PC2 immunoreactivity in neighbouring α-cells acts as a positive control. In donors with type 2 diabetes, β-cells had elevated PC2 immunoreactivity, suggesting that aberrant PC2 expression may contribute to impaired proinsulin processing in β-cells of patients with diabetes. To support histological findings using a biochemical approach, human islets were used for pulse-chase experiments. Despite inhibition of PC2 function by temperature blockade, brefeldin-A, chloroquine, and multiple inhibitors that blocked production of mature glucagon from proglucagon, β-cells retained the ability to produce mature insulin. Conversely, suppression of PC1/3 blocked processing of proinsulin but not proglucagon. By demonstrating that healthy human β-cells process proinsulin by PC1/3 but not PC2 we suggest that there is a need to revise the longstanding theory of proinsulin processing.

Milk production may involve a transient development of insulin resistance in non-mammary tissues to support redistribution of maternal macronutrients to match the requirements of the lactating mammary gland. In the present study, adipose and liver metabolic responses were measured in the fasting state and during a 2-step (10 and 20 mU/m²/min) hyperinsulinemic-euglycemic clamp with stable isotopes, in 6-week postpartum women who were lactating (n=12) or formula-feeding (n=6) their infants and who were closely matched for baseline characteristics (e.g., parity, body composition, intrahepatic lipid). When controlling for the low insulin concentrations of both groups, the lactating women exhibited a fasting rate of endogenous glucose production (EGP) that was 2.6-fold greater, and a lipolysis rate that was 2.3-fold greater than the formula-feeding group. During the clamp, the groups exhibited similar suppression rates of EGP and lipolysis. In the lactating women only, higher prolactin concentrations were associated with greater suppression rates of lipolysis, lower intrahepatic lipid and plasma triacylglycerol concentrations. These data suggest that whole-body alterations in glucose transport may be organ specific and facilitate nutrient partitioning during lactation. Recapitulating a shift toward noninsulin-mediated glucose uptake could be an early postpartum strategy to enhance lactation success in women at risk for delayed onset of milk production.

Over the last several years it has become clear that higher order assemblies on membranes, exemplified by signalosomes, are a paradigm for the regulation of many membrane signaling processes. We have recently combined two-color direct stochastic optical reconstruction microscopy (dSTORM) with the (Clus-DoC) algorithm that combines cluster detection and colocalization analysis to observe the organization of 5-lipoxygenase (5-LO) and 5-lipoxygenase–activating protein (FLAP) into higher order assemblies on the nuclear envelope of mast cells; these assemblies were linked to leukotriene (LT) C4 production. In this study we investigated whether higher order assemblies of 5-LO and FLAP included cytosolic phospholipase A2 (cPLA2) and were linked to LTB4 production in murine neutrophils. Using two- and three-color dSTORM supported by fluorescence lifetime imaging microscopy we identified higher order assemblies containing 40 molecules (median) (IQR: 23, 87) of 5-LO, and 53 molecules (62, 156) of FLAP monomer. 98 (18, 154) molecules of cPLA2 were clustered with 5-LO, and 77 (33, 114) molecules of cPLA2 were associated with FLAP. These assemblies were tightly linked to LTB4 formation. The activation-dependent close associations of cPLA2, FLAP, and 5-LO in higher order assemblies on the nuclear envelope support a model in which arachidonic acid is generated by cPLA2 in apposition to FLAP, facilitating its transfer to 5-LO to initiate LT synthesis.

Lena Eliasson
May 1, 2020; 69:804-812
Small Noncoding RNAs in Diabetes