Epithelial and subepithelial players in chronic intestinal disease

The intestinal epithelium and the subepithelial layers form the primary barrier in the human gut. It is responsible for the absorption of essential nutrients from the diet and protects against potentially harmful and/or infections substances in the gut lumen. Many chronic intestinal diseases are caused by the toxic effects of such harmful substances on the intestinal epithelium and subepithelial layers, which results in intestinal dysfunction, including intestinal inflammation, fibrosis and cancer. Among them, cigarette smoking is a well-known risk factor for developing (fibrotic) Crohn's disease and colon cancer. However, in what way cigarette smoke directly affects the human intestinal epithelial and subepithelial cells functioning is not really known. This thesis focuses on the effect of cigarette smoke on the human intestinal epithelium and subepithelial cells (myofibroblasts) and analyzed the effect of an antifibrotic drug, pirfenidone, on the fibrogenic potential of intestinal myofibroblasts. This thesis encompasses four parts: 1) the effect of cigarette smoke extract (CSE) on epithelial cell morphogenesis, regeneration, polarity and barrier function; 2) the effect of cigarette smoking/CSE on the expression of immunomodulatory vascular adhesion protein-1 (VAP-1) in inflammatory bowel disease patients and primary human intestinal fibroblasts (p-hIFs); 3) identification and characterization of a subtype of enteroendocrine cells that expresses immunomodulatory VAP-1; and 4) anti-fibrotic function of pirfenidone on p-hIFs and underlying mechanism involved in it. This work displays the value of employing human intestinal organoid and p-hIFs for advancing intestinal chronic disease research and drug development as preclinical tools

A glycolysis-related gene signatures in diffuse large B-Cell lymphoma predicts prognosis and tumor immune microenvironment

Background: Diffuse large B-cell lymphoma (DLBCL) is the most common type of lymphoma which that highly aggressive and heterogeneous. Glycolysis has been implicated in the regulation of tumor microenvironment (TME) and development. In this study, we aimed to establish a glycolysis-related prognostic model for the risk stratification, prognosis prediction, and immune landscape evaluation in patients with DLBCL.Methods: Three independent datasets GSE181063, GSE10846, and GSE53786 containing gene expression profiles and clinical data were downloaded from the Gene Expression Omnibus (GEO) database. The glycolysis-related prognostic model was developed with Cox and Least Absolute Shrinkage and Selector Operation (LASSO) regression and validated. A nomogram integrating clinical factors and glycolytic risk scores was constructed. The composition of the TME was analyzed with the ESTIMATE algorithm and single-sample gene set enrichment analysis (ssGSEA).Results: A glycolytic risk model containing eight genes was developed. The area under the receiver operating characteristic (ROC) curve (AUC) for the 1-, 3-, and 5-year was 0.718, 0.695, and 0.688, respectively. Patients in the high-risk group had significantly lower immune scores, elevated tumor purity, and poorer survival compared with those in the low-risk group. The nomogram constructed based on glycolytic risk score, age, Eastern Cooperative Oncology Group performance status (ECOG-PS), use of rituximab, and cell of origin (COO) displayed better prediction performance compared with the International Prognostic Index (IPI) in DLBCL. The glycolytic risk score was negatively correlated with the infiltration level of activated CD8 T cells, activated dendritic cells, natural killer cells, and macrophages and immune checkpoint molecules including PD-L2, CTLA4, TIM-3, TIGIT, and B7-H3.Conclusion: These results suggested that the glycolytic risk model could accurately and stably predict the prognosis of patients with DLBCL and might unearth the possible explanation for the glycolysis-related poor prognosis

Cascaded Multi-task Adaptive Learning Based on Neural Architecture Search

Cascading multiple pre-trained models is an effective way to compose an end-to-end system. However, fine-tuning the full cascaded model is parameter and memory inefficient and our observations reveal that only applying adapter modules on cascaded model can not achieve considerable performance as fine-tuning. We propose an automatic and effective adaptive learning method to optimize end-to-end cascaded multi-task models based on Neural Architecture Search (NAS) framework. The candidate adaptive operations on each specific module consist of frozen, inserting an adapter and fine-tuning. We further add a penalty item on the loss to limit the learned structure which takes the amount of trainable parameters into account. The penalty item successfully restrict the searched architecture and the proposed approach is able to search similar tuning scheme with hand-craft, compressing the optimizing parameters to 8.7% corresponding to full fine-tuning on SLURP with an even better performance

Pirfenidone Inhibits Cell Proliferation and Collagen I Production of Primary Human Intestinal Fibroblasts

Intestinal fibrosis is a common complication of inflammatory bowel disease. So far, there is no safe and effective drug for intestinal fibrosis. Pirfenidone is an anti-fibrotic compound available for the treatment of idiopathic pulmonary fibrosis. Here, we explored the anti-proliferative and anti-fibrotic properties of pirfenidone on primary human intestinal fibroblasts (p-hIFs). p-hIFs were cultured in the absence and presence of pirfenidone. Cell proliferation was measured by a real-time cell analyzer (xCELLigence) and BrdU incorporation. Cell motility was monitored by live cell imaging. Cytotoxicity and cell viability were analyzed by Sytox green, Caspase-3 and Water Soluble Tetrazolium Salt-1 (WST-1) assays. Gene expression of fibrosis markers was determined by quantitative reverse transcription PCR (RT-qPCR). The mammalian target of rapamycin (mTOR) signaling was analyzed by Western blotting and type I collagen protein expression additionally by immunofluorescence microscopy. Pirfenidone dose-dependently inhibited p-hIF proliferation and motility, without inducing cell death. Pirfenidone suppressed mRNA levels of genes that contribute to extracellular matrix production, as well as basal and TGF-beta 1-induced collagen I protein production, which was associated with inhibition of the rapamycin-sensitive mTOR/p70S6K pathway in p-hIFs. Thus, pirfenidone inhibits the proliferation of intestinal fibroblasts and suppresses collagen I production through the TGF-beta 1/mTOR/p70S6K signaling pathway, which might be a novel and safe anti-fibrotic strategy to treat intestinal fibrosis

Identifying the proton loading site cluster in the ba₃ cytochrome c oxidase that loads and traps protons

Cytochrome c Oxidase (CcO) is the terminal electron acceptor in aerobic respiratory chain, reducing O₂ to water. The released free energy is stored by pumping protons through the protein, maintaining the transmembrane electrochemical gradient. Protons are held transiently in a proton loading site (PLS) that binds and releases protons driven by the electron transfer reaction cycle. Multi-Conformation Continuum Electrostatics (MCCE) was applied to crystal structures and Molecular Dynamics snapshots of the B-type Thermus thermophilus CcO. Six residues are identified as the PLS, binding and releasing protons as the charges on heme b and the binuclear center are changed: the heme a₃ propionic acids, Asp287, Asp372, His376 and Glu126B. The unloaded state has one proton and the loaded state two protons on these six residues. Different input structures, modifying the PLS conformation, show different proton distributions and result in different proton pumping behaviors. One loaded and one unloaded protonation states have the loaded/unloaded states close in energy so the PLS binds and releases a proton through the reaction cycle. The alternative proton distributions have state energies too far apart to be shifted by the electron transfers so are locked in loaded or unloaded states. Here the protein can use active states to load and unload protons, but has nearby trapped states, which stabilize PLS protonation state, providing new ideas about the CcO proton pumping mechanism. The distance between the PLS residues Asp287 and His376 correlates with the energy difference between loaded and unloaded states

Biomass-based carbon materials for CO2 capture:A review

Carbon capture and sequestration technologies are essential to reduce CO2 emissions which are responsible for global warming. Carbon-based materials can play an important role in the reduction of CO2 emissions. These materials are normally produced from biomass through technologies such as pyrolysis and hydrothermal carbonization. The type of biomass feedstock and biomass conversion conditions can significantly affect the textual properties and surface chemistry of the carbon materials. Various modification methods such as material activation or N-doping can improve the properties of carbon materials to obtain better CO2 capture effects. This review summarizes recently reported research in the areas of using biomass-based materials for CO2 capture. The technologies of biomass conversion to carbon materials and modification of the carbon materials are critically analyzed. Meanwhile, the mechanisms of the CO2 capture process and research of different modification carbon materials for CO2 capture are also discussed. Finally, potential future research directions are suggested to promote carbon capture using biomass-based materials

Protective effect of ursodeoxycholic acid on COVID-19 in patients with chronic liver disease

ObjectiveUrsodeoxycholic acid (UDCA) may reduce susceptibility to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection by downregulating angiotensin-converting enzyme 2 (ACE2), based on recent experimental investigation. This study aimed to determine the potential protective effect of UDCA against SARS-CoV-2 infection in patients with chronic liver disease.MethodsPatients with chronic liver disease receiving UDCA (taking UDCA ≥1 month) at Beijing Ditan Hospital between January 2022 and December 2022 were consecutively enrolled. These patients were matched in a 1:1 ratio to those with liver disease not receiving UDCA during the same period by using a propensity score matching analysis with nearest neighbor matching algorithm. We conducted a phone survey of coronavirus disease 2019 (COVID-19) infection during the early phase of the pandemic liberation (from 15 December 2022 to 15 January 2023). The risk of COVID-19 was compared in two matched cohorts of 225 UDCA users and 225 non-UDCA users based on patient self-report.ResultsIn the adjusted analysis, the control group was superior to the UDCA group in COVID-19 vaccination rates and liver function indicators, including γ-glutamyl transpeptidase and alkaline phosphatase (p < 0.05). UDCA was associated with a lower incidence of SARS-CoV-2 infection (UDCA 85.3% vs. control 94.2%, p = 0.002), more mild cases (80.0% vs. 72.0%, p = 0.047), and shorter median time from infection to recovery (5 vs. 7 days, p < 0.001). Logistic regression analysis showed that UDCA was a significant protective factor against COVID-19 infection (OR: 0.32, 95%CI: 0.16–0.64, p = 0.001). Furthermore, diabetes mellitus (OR: 2.48, 95%CI: 1.11–5.54, p = 0.027) and moderate/severe infection (OR: 8.94, 95%CI: 1.07–74.61, p = 0.043) were more likely to prolong the time from infection to recovery.ConclusionUDCA therapy may be beneficial in reducing COVID-19 infection risk, alleviating symptoms, and shortening the recovery time in patients with chronic liver disease. However, it should be emphasized that the conclusions were based on patient self-report rather than classical COVID-19 detection by experimental investigations. Further large clinical and experimental studies are needed to validate these findings

Pathway and kinetics of cyhalothrin biodegradation by Bacillus thuringiensis strain ZS-19

10.1038/srep08784Scientific Reports