Colonocytes possess a specific carrier-mediated uptake process for the microbiota-generated thiamin (vitamin B1) pyrophosphate (TPP) that involves the TPP transporter (TPPT; product of the SLC44A4 gene). Little is known about the effect of exogenous factors (including enteric pathogens) on the colonic TPP uptake process. Our aim in this study was to investigate the effect of Enterohemorrhagic Escherichia coli (EHEC) infection on colonic uptake of TPP. We used human-derived colonic epithelial NCM460 cells and mice in our investigation. The results showed that infecting NCM460 cells with live EHEC (but not with heat-killed EHEC, EHEC culture supernatant, or with non-pathogenic E. Coli) to lead to a significant inhibition in carrier-mediated TPP uptake, as well as in level of expression of the TPPT protein and mRNA. Similarly, infecting mice with EHEC led to a significant inhibition in colonic TPP uptake and in level of expression of TPPT protein and mRNA. The inhibitory effect of EHEC on TPP uptake by NCM460 was found to be associated with reduction in the rate of transcription of the SLC44A4 gene as indicated by the significant reduction in the activity of the SLC44A4 promoter transfected into EHEC infected cells. The latter was also associated with a marked reduction in the level of expression of the transcription factors CREB-1 and ELF3, which are known to drive the activity of the SLC44A4 promoter. Finally, blocking the ERK1/2 and NF-kB signaling pathways in NCM460 cells significantly reversed the level of EHEC inhibition in TPP uptake and TPPT expression. Collectively, these findings show, for the first time, that EHEC infection significantly inhibit colonic uptake of TPP, and that this effect appears to be exerted at the level of SLC44A4 transcription and involves the ERK1/2 and NF-kB signaling pathways.

Background: The monitoring and analysis of quasi-periodic biological signals such as electrocardiography (ECG), intracranial pressure (ICP), and cerebral blood flow velocity (CBFV) waveforms plays an important role in the early detection of adverse patient events and contributes to improved care management in the intensive care unit (ICU). This work provides a quantitative evaluation of existing computational frameworks for the automatic extraction of peaks within ICP waveforms. Methods: Peak detection techniques based on state-of-the-art machine learning models were evaluated in terms of robustness to varying levels of noise. Evaluation was performed on a dataset of ICP signals assembled from 700 hours of monitoring from 64 neurosurgical patients. The groundtruth of the peak locations was established manually on a subset of 13,611 pulses. Additional evaluation was performed using a simulated dataset of ICP with controlled temporal dynamics and noise. Results: The quantitative analysis of peak detection algorithms applied to individual waveforms indicates that all techniques provide acceptable accuracy (RMSE <= 0.15) without noise. In presence of higher level of noise, however, only Kernel ridge regression and Random forest remains below that error threshold while the performance of other techniques significantly deteriorates. Our experiments also demonstrated that tracking methods such as Bayesian inference and LSTM can be applied in a continuous fashion and provide additional robustness in situations where single pulse analysis methods tend to fail such as in presence of missing data. Conclusion: While machine learning-based peak detection methods require manually labeled data for training, these models outperform conventional signal processing ones based on handcrafted rules and should be considered for peak detection in modern frameworks. In particular, peak tracking methods that incorporate temporal information between successive periods of the signals have demonstrated in our experiments to provide more robustness to temporary artifacts that commonly arise as part of the monitoring setup in the NICU.

Introduction Peroxisome proliferator activated receptor gamma (PPAR‐γ) plays an important role in regulating intestinal inflammation. PPAR‐γ is expressed in many tissues in the body but high amount is found in adipose tissue and colon. Therefore, PPAR‐γ ligands offer drug‐targeting system that can be exploited for treating inflammatory bowel diseases (IBDs). IBD prevalence is on the rise globally. Current mainstream therapies for IBD offer protection but with many side effects, therefore, up to 30% IBD patients turn to alternate therapy using dietary phytochemicals. α‐Bisabolol, a naturally occurring dietary sesquiterpene, isolated from Matricaria chamomilla has been demonstrated to have anti‐inflammatory properties. Initial docking studies reveal that it is a potent activator of PPAR‐γ transcription factor. Aim Therefore, the main aim of this study was to investigate α‐Bisabolol’s anti‐inflammatory property using both in vivo and in vitro experimental models of colon inflammation. Methodology C57BL/6J black mice were administered with 2% dextran sodium sulfate (DSS) in drinking water for 7days to induce colitis. The treatment group received α‐Bisabolol at 50 & 100 mg/kg body wt and compared with control and DSS along with a positive control drug. The disease activity index (DAI), colon length, myeloperoxidase (MPO) and histology was performed. Pro‐inflammatory cytokines (IL‐1β, IL‐6, and TNF‐α) level was measured using ELISA, and mRNA using real time PCR. Pro‐inflammatory mediators such as Cox‐2, iNOS expression was also measured at both protein and mRNA levels. PPAR‐γ and NF‐κB interaction were evaluated using colonic epithelial cell cytoplasm and nuclear fractions. Human colon carcinoma cell line, HT‐29 was used for in vitro studies. HT‐29 cells were cultured in 10% FBS containing DMEM media and were stimulated using TNF‐α (1ng/ml) to mimic inflammation. Various concentrations of α‐Bisabolol effect was evaluated on pro‐inflammatory cytokines such as GRO‐α, IL‐8, TNF‐α, COX‐2, and iNOS mRNA levels using real time PCR. Results α‐Bisabolol treatment significantly (p<0.01) decreased DAI, MPO level and restored colon length in a dose dependent manner in DSS treated group. Histological scoring for colonic crypt damage and inflammation was significantly (p<0.001) improved upon α‐Bisabolol treatment. α‐Bisabolol treatment also inhibited the pro‐inflammatory cytokines (IL‐1β, IL‐6 and TNF‐α) significantly (p<0.01) both at protein and mRNA level. α‐Bisabolol significantly inhibited COX‐2, and iNOS both at the protein and mRNA levels. α‐Bisabolol also activated PPAR‐γ protein expression in a dose dependent manner and also inhibited NF‐κB expression. α‐Bisabolol significantly (p<0.01) decreased pro‐inflammatory cytokine (GRO‐α, IL‐8, TNF‐α, COX‐2, and iNOS) mRNA expression when HT‐29 cells were challenged with TNF‐α. Support or Funding Information This study is supported by United Arab Emirates University, Zayed Center for Health Sciences, Center Based Interdisciplinary grant awarded to Dr Sandeep B Subramanya. Grant #31R230

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