Serum levels of advanced glycation end products and their receptors sRAGE and Galectin-3 in chronic pancreatitis.

BACKGROUND: /Objectives: AGE and their receptors like RAGE and Galectin-3 can activate inflammatory pathways and have been associated with chronic inflammatory diseases. Several studies investigated the role of AGE, Galectin-3 and sRAGE in pancreatic diseases, whereas no comprehensive data for chronic pancreatitis (CP) are available. METHODS: Serum samples from CP patients without an active inflammatory process (85 ACP; 26 NACP patients) and 40 healthy controls were collected. Levels of AGE, sRAGE and Galectin-3 were measured by ELISA. To exclude potential influences of previously described RAGE SNPs on detected serum levels, we analyzed variants rs207128, rs207060, rs1800625, and rs1800624 by melting curve technique in 378 CP patients and 338 controls. RESULTS: AGE and Galectin-3 serum levels were significantly elevated in both ACP and NACP patients compared to controls (AGE: 56.61 ± 3.043 vs. 31.71 ± 2.308 ng/mL; p < 0.001; Galectin-3: 16.63 ± 0.6297 vs. 10.81 ± 0.4835 ng/mL; p < 0.001). In contrast, mean serum sRAGE levels were significantly reduced in CP patients compared to controls (sRAGE: 829.7 ± 37.10 vs. 1135 ± 55.74 ng/mL; p < 0.001). All results were consistent after correction for gender, age and diabetes mellitus. No genetic association with CP was found. CONCLUSIONS: Our extensive analysis demonstrated the importance of aging related pathways in the pathogenesis of CP. As the results were consistent in ACP and NACP, both entities most likely share common pathomechanisms. Most probably the involved pathways are a general hallmark of an inflammatory state in CP that is even present in symptom-free intervals.

Genome-Wide Transcriptional Response to Varying RpoS Levels in Escherichia coli K-12.

The alternative sigma factor RpoS is a central regulator of many stress responses in Escherichia coli The level of functional RpoS differs depending on the stress. The effect of these differing concentrations of RpoS on global transcriptional responses remains unclear. We investigated the effect of RpoS concentration on the transcriptome during stationary phase in rich media. We found that 23% of genes in the E. coli genome are regulated by RpoS, and we identified many RpoS-transcribed genes and promoters. We observed three distinct classes of response to RpoS by genes in the regulon: genes whose expression changes linearly with increasing RpoS level, genes whose expression changes dramatically with the production of only a little RpoS ("sensitive" genes), and genes whose expression changes very little with the production of a little RpoS ("insensitive"). We show that sequences outside the core promoter region determine whether an RpoS-regulated gene is sensitive or insensitive. Moreover, we show that sensitive and insensitive genes are enriched for specific functional classes and that the sensitivity of a gene to RpoS corresponds to the timing of induction as cells enter stationary phase. Thus, promoter sensitivity to RpoS is a mechanism to coordinate specific cellular processes with growth phase and may also contribute to the diversity of stress responses directed by RpoS.IMPORTANCE The sigma factor RpoS is a global regulator that controls the response to many stresses in Escherichia coli Different stresses result in different levels of RpoS production, but the consequences of this variation are unknown. We describe how changing the level of RpoS does not influence all RpoS-regulated genes equally. The cause of this variation is likely the action of transcription factors that bind the promoters of the genes. We show that the sensitivity of a gene to RpoS levels explains the timing of expression as cells enter stationary phase and that genes with different RpoS sensitivities are enriched for specific functional groups. Thus, promoter sensitivity to RpoS is a mechanism that coordinates specific cellular processes in response to stresses.

Computer-aided diagnosis of hepatocellular carcinoma fusing imaging and structured health data.

INTRODUCTION: Hepatocellular carcinoma is the prevalent primary liver cancer, a silent disease that killed 782,000 worldwide in 2018. Multimodal deep learning is the application of deep learning techniques, fusing more than one data modality as the model's input. PURPOSE: A computer-aided diagnosis system for hepatocellular carcinoma developed with multimodal deep learning approaches could use multiple data modalities as recommended by clinical guidelines, and enhance the robustness and the value of the second-opinion given to physicians. This article describes the process of creation and evaluation of an algorithm for computer-aided diagnosis of hepatocellular carcinoma developed with multimodal deep learning techniques fusing preprocessed computed-tomography images with structured data from patient Electronic Health Records. RESULTS: The classification performance achieved by the proposed algorithm in the test dataset was: accuracy = 86.9%, precision = 89.6%, recall = 86.9% and F-Score = 86.7%. These classification performance metrics are closer to the state-of-the-art in this area and were achieved with data modalities which are cheaper than traditional Magnetic Resonance Imaging approaches, enabling the use of the proposed algorithm by low and mid-sized healthcare institutions. CONCLUSION: The classification performance achieved with the multimodal deep learning algorithm is higher than human specialists diagnostic performance using only CT for diagnosis. Even though the results are promising, the multimodal deep learning architecture used for hepatocellular carcinoma prediction needs more training and test processes using different datasets before the use of the proposed algorithm by physicians in real healthcare routines. The additional training aims to confirm the classification performance achieved and enhance the model's robustness.

Common variants in glyoxalase I do not increase chronic pancreatitis risk.

INTRODUCTION: Chronic pancreatitis (CP) may be caused by oxidative stress. An important source of reactive oxygen species (ROS) is the methylglyoxal-derived formation of advanced glycation endproducts (AGE). Methylglyoxal is detoxified by Glyoxalase I (GLO1). A reduction in GLO1 activity results in increased ROS. Single nucleotide polymorphisms (SNPs) of GLO1 have been linked to various inflammatory diseases. Here, we analyzed whether common GLO1 variants are associated with alcoholic (ACP) and non-alcoholic CP (NACP). METHODS: Using melting curve analysis, we genotyped a screening cohort of 223 ACP, 218 NACP patients, and 328 controls for 11 tagging SNPs defined by the SNPinfo LD TAG SNP Selection tool and the functionally relevant variant rs4746. For selected variants the cohorts were extended to up to 1,441 patient samples. RESULTS: In the ACP cohort, comparison of genotypes for rs1937780 between patients and controls displayed an ambiguous result in the screening cohort (p = 0.08). However, in the extended cohort of 1,441 patients no statistically significant association was found for the comparison of genotypes (p = 0.11), nor in logistic regression analysis (p = 0.214, OR 1.072, 95% CI 0.961-1.196). In the NACP screening cohort SNPs rs937662, rs1699012, and rs4746 displayed an ambiguous result when patients were compared to controls in the recessive or dominant model (p = 0.08, 0.08, and 0.07, respectively). Again, these associations were not confirmed in the extended cohorts (rs937662, dominant model: p = 0.07, logistic regression: p = 0.07, OR 1.207, 95% CI 0.985-1.480) or in the replication cohorts for rs4746 (Germany, p = 0.42, OR 1.080, 95% CI 0.673-1.124; France, p = 0.19, OR 0.90, 95% CI 0.76-1.06; China, p = 0.24, OR 1.18, 95% CI 0.90-1.54) and rs1699012 (Germany, Munich; p = 0.279, OR 0.903, 95% CI 0.750-1.087). CONCLUSIONS: Common GLO1 variants do not increase chronic pancreatitis risk.

Limitaciones del peso y talla autorreferidos / Self-reported height and weight limitations

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