Animal Inhalation Models to Investigate Modulation of Inflammatory Bowel Diseases

Inflammatory bowel diseases (IBDs) comprise primarily two disease manifestations, ulcerative colitis (UC) and Crohn’s disease (CD), each with distinctive clinical and pathological features. Environmental and clinical factors strongly affect the development and clinical outcomes of IBDs. Among environmental factors, cigarette smoke (CS) is considered the most important risk factor for CD, while it attenuates the disease course of UC. Various animal models have been used to assess the impact of CS on intestinal pathophysiology. This chapter examines the suitability of animal inhalation/smoke exposure models for assessing the contrary effects of CS on UC and CD. It presents an updated literature review of IBD mouse models and a description of possible mechanisms relevant to relationships between IBD and smoking. In addition, it summarises various technical inhalation approaches, in the context of mouse disease models of IBD

Enhancement of COPD Biological Networks Using a Web-Based Collaboration Interface

The construction and application of biological network models is an approach that offers a holistic way to understand biological processes involved in disease. Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease of the airways for which therapeutic options currently are limited after diagnosis, even in its earliest stage. COPD network models are important tools to better understand the biological components and processes underlying initial disease development. With the increasing amounts of literature that are now available, crowdsourcing approaches offer new forms of collaboration for researchers to review biological findings, which can be applied to the construction and verification of complex biological networks. We report the construction of 50 biological network models relevant to lung biology and early COPD using an integrative systems biology and collaborative crowd-verification approach. By combining traditional literature curation with a data-driven approach that predicts molecular activities from transcriptomics data, we constructed an initial COPD network model set based on a previously published non-diseased lung-relevant model set. The crowd was given the opportunity to enhance and refine the networks on a website (https://bionet.sbvimprover.com/) and to add mechanistic detail, as well as critically review existing evidence and evidence added by other users, so as to enhance the accuracy of the biological representation of the processes captured in the networks. Finally, scientists and experts in the field discussed and refined the networks during an in-person jamboree meeting. Here, we describe examples of the changes made to three of these networks: Neutrophil Signaling, Macrophage Signaling, and Th1-Th2 Signaling. We describe an innovative approach to biological network construction that combines literature and data mining and a crowdsourcing approach to generate a comprehensive set of COPD-relevant models that can be used to help understand the mechanisms related to lung pathobiology. Registered users of the website can freely browse and download the networks

Construction of a computable cell proliferation network focused on non-diseased lung cells

<p>Abstract</p> <p>Background</p> <p>Critical to advancing the systems-level evaluation of complex biological processes is the development of comprehensive networks and computational methods to apply to the analysis of systems biology data (transcriptomics, proteomics/phosphoproteomics, metabolomics, etc.). Ideally, these networks will be specifically designed to capture the normal, non-diseased biology of the tissue or cell types under investigation, and can be used with experimentally generated systems biology data to assess the biological impact of perturbations like xenobiotics and other cellular stresses. Lung cell proliferation is a key biological process to capture in such a network model, given the pivotal role that proliferation plays in lung diseases including cancer, chronic obstructive pulmonary disease (COPD), and fibrosis. Unfortunately, no such network has been available prior to this work.</p> <p>Results</p> <p>To further a systems-level assessment of the biological impact of perturbations on non-diseased mammalian lung cells, we constructed a lung-focused network for cell proliferation. The network encompasses diverse biological areas that lead to the regulation of normal lung cell proliferation (Cell Cycle, Growth Factors, Cell Interaction, Intra- and Extracellular Signaling, and Epigenetics), and contains a total of 848 nodes (biological entities) and 1597 edges (relationships between biological entities). The network was verified using four published gene expression profiling data sets associated with measured cell proliferation endpoints in lung and lung-related cell types. Predicted changes in the activity of core machinery involved in cell cycle regulation (RB1, CDKN1A, and MYC/MYCN) are statistically supported across multiple data sets, underscoring the general applicability of this approach for a network-wide biological impact assessment using systems biology data.</p> <p>Conclusions</p> <p>To the best of our knowledge, this lung-focused Cell Proliferation Network provides the most comprehensive connectivity map in existence of the molecular mechanisms regulating cell proliferation in the lung. The network is based on fully referenced causal relationships obtained from extensive evaluation of the literature. The computable structure of the network enables its application to the qualitative and quantitative evaluation of cell proliferation using systems biology data sets. The network is available for public use.</p

Recent advances in the development of portable technologies and commercial products to detect Δ9-tetrahydrocannabinol in biofluids: a systematic review

Abstract Background The primary components driving the current commercial fascination with cannabis products are phytocannabinoids, a diverse group of over 100 lipophilic secondary metabolites derived from the cannabis plant. Although numerous phytocannabinoids exhibit pharmacological effects, the foremost attention has been directed towards Δ9-tetrahydrocannabinol (THC) and cannabidiol, the two most abundant phytocannabinoids, for their potential human applications. Despite their structural similarity, THC and cannabidiol diverge in terms of their psychotropic effects, with THC inducing notable psychological alterations. There is a clear need for accurate and rapid THC measurement methods that offer dependable, readily accessible, and cost-effective analytical information. This review presents a comprehensive view of the present state of alternative technologies that could potentially facilitate the creation of portable devices suitable for on-site usage or as personal monitors, enabling non-intrusive THC measurements. Method A literature survey from 2017 to 2023 on the development of portable technologies and commercial products to detect THC in biofluids was performed using electronic databases such as PubMed, Scopus, and Google Scholar. A systematic review of available literature was conducted using Preferred Reporting Items for Systematic. Reviews and Meta-analysis (PRISMA) guidelines. Results Eighty-nine studies met the selection criteria. Fifty-seven peer-reviewed studies were related to the detection of THC by conventional separation techniques used in analytical laboratories that are still considered the gold standard. Studies using optical (n = 12) and electrochemical (n = 13) portable sensors and biosensors were also identified as well as commercially available devices (n = 7). Discussion The landscape of THC detection technology is predominantly shaped by immunoassay tests, owing to their established reliability. However, these methods have distinct drawbacks, particularly for quantitative analysis. Electrochemical sensing technology holds great potential to overcome the challenges of quantification and present a multitude of advantages, encompassing the possibility of miniaturization and diverse modifications to amplify sensitivity and selectivity. Nevertheless, these sensors have considerable limitations, including non-specific interactions and the potential interference of compounds and substances existing in biofluids. Conclusion The foremost challenge in THC detection involves creating electrochemical sensors that are both stable and long-lasting while exhibiting exceptional selectivity, minimal non-specific interactions, and decreased susceptibility to matrix interferences. These aspects need to be resolved before these sensors can be successfully introduced to the market

Physicochemical studies of direct interactions between lung surfactant and components of electronic cigarettes mixtures

Direct physicochemical interactions between the major components of electronic cigarette liquids (e-liquids): glycerol (VG) and propylene glycol (PG), and lung surfactant (LS) were studied by determining the dynamic surface tension under a simulated breathing cycle using drop shape method. The studies were performed for a wide range of concentrations based on estimated doses of e-liquid aerosols (up to 2500 × the expected nominal concentrations) and for various VG/PG ratios. The results are discussed as relationships among mean surface tension, surface tension amplitude, and surface rheological properties (dilatational elasticity and viscosity) versus concentration and composition of e-liquid. The results showed that high local concentrations (>200 × higher than the estimated average dose after a single puffing session) may induce measurable changes in biophysical activity of LS; however, only ultra-high e-liquid concentrations inactivated the surfactant. Physiochemical characterization of e-liquids provide additional insights for the safety assessment of electronic nicotine delivery systems (ENDS)

Systems Approaches Evaluating the Perturbation of Xenobiotic Metabolism in Response to Cigarette Smoke Exposure in Nasal and Bronchial Tissues

Capturing the effects of exposure in a specific target organ is a major challenge in risk assessment. Exposure to cigarette smoke (CS) implicates the field of tissue injury in the lung as well as nasal and airway epithelia. Xenobiotic metabolism in particular becomes an attractive tool for chemical risk assessment because of its responsiveness against toxic compounds, including those present in CS. This study describes an efficient integration from transcriptomic data to quantitative measures, which reflect the responses against xenobiotics that are captured in a biological network model. We show here that our novel systems approach can quantify the perturbation in the network model of xenobiotic metabolism. We further show that this approach efficiently compares the perturbation upon CS exposure in bronchial and nasal epithelial cells in vivo samples obtained from smokers. Our observation suggests the xenobiotic responses in the bronchial and nasal epithelial cells of smokers were similar to those observed in their respective organotypic models exposed to CS. Furthermore, the results suggest that nasal tissue is a reliable surrogate to measure xenobiotic responses in bronchial tissue

Systematic Verification of Upstream Regulators of a Computable Cellular Proliferation Network Model on Non-Diseased Lung Cells Using a Dedicated Dataset

We recently constructed a computable cell proliferation network (CPN) model focused on lung tissue to unravel complex biological processes and their exposure-related perturbations from molecular profiling data. The CPN consists of edges and nodes representing upstream controllers of gene expression largely generated from transcriptomics datasets using Reverse Causal Reasoning (RCR). Here, we report an approach to biologically verify the correctness of upstream controller nodes using a specifically designed, independent lung cell proliferation dataset. Normal human bronchial epithelial cells were arrested at G1/S with a cell cycle inhibitor. Gene expression changes and cell proliferation were captured at different time points after release from inhibition. Gene set enrichment analysis demonstrated cell cycle response specificity via an overrepresentation of proliferation related gene sets. Coverage analysis of RCR-derived hypotheses returned statistical significance for cell cycle response specificity across the whole model as well as for the Growth Factor and Cell Cycle sub-network models

Fractionation and Extraction Optimization of Potentially Valuable Compounds and Their Profiling in Six Varieties of Two <i>Nicotiana</i> Species

There is an increasingly urgent call to shift industrial processes from fossil fuel feedstock to sustainable bio-based resources. This change becomes of high importance considering new budget requirements for a carbon-neutral economy. Such a transformation can be driven by traditionally used plants that are able to produce large amounts of valuable biologically relevant secondary metabolites. Tobacco plants can play a leading role in providing value-added products in remote areas of the world. In this study, we propose a non-exhaustive list of compounds with potential economic interest that can be sourced from the tobacco plant. In order to optimize extraction methodologies, we first analyzed their physico-chemical properties using rapid solubility tests and high-resolution microfractionation techniques. Next, to identify an optimal extraction for a selected list of compounds, we compared 13 different extraction method–solvent combinations. We proceeded with profiling some of these compounds in a total of six varieties from Nicotiana tabacum and Nicotiana rustica species, identifying the optimal variety for each. The estimated expected yields for each of these compounds demonstrate that tobacco plants can be a superior source of valuable compounds with diverse applications beyond nicotine. Among the most interesting results, we found high variability of anatabine content between species and varieties, ranging from 287 to 1699 µg/g. In addition, we found that CGA (1305 µg/g) and rutin (7910 µg/g) content are orders of magnitude lower in the Burley variety as compared to all others