Involvement of the gut microbiota in cancer cachexia.

Cancer cachexia, or the unintentional loss of body weight in cancer patients, is a multi-organ and multi-factorial syndrome with a complex and largely unknown etiology; however, metabolic dysfunction and inflammation remain hallmarks of cancer-associated wasting. While cachexia manifests with muscle and adipose tissue loss, perturbations to the gastrointestinal tract may serve as the front line for both impaired nutrient absorption and immune activating gut dysbiosis. Investigations into the gut microbiota have exploded within the past 2 decades, demonstrating multiple gut-tissue axes; however, the link between adipose and skeletal muscle wasting and the gut microbiota with cancer is only beginning to be understood. Further, the most used anti-cancer drugs (e.g. chemotherapy, immune checkpoint inhibitors) negatively impact gut homeostasis, potentially exacerbating wasting and contributing to poor patient outcomes and survival. In this current review, we 1) highlight our current understanding of the microbial changes that occur with cachexia, 2) discuss how microbial changes may contribute to adipose and skeletal muscle wasting, and 3) outline study design considerations needed when examining the role of the microbiota in cancer-induced cachexia.

Enabling personalised disease diagnosis by combining a patient's time-specific gene expression profile with a biomedical knowledge base.

BACKGROUND: Recent developments in the domain of biomedical knowledge bases (KBs) open up new ways to exploit biomedical knowledge that is available in the form of KBs. Significant work has been done in the direction of biomedical KB creation and KB completion, specifically, those having gene-disease associations and other related entities. However, the use of such biomedical KBs in combination with patients' temporal clinical data still largely remains unexplored, but has the potential to immensely benefit medical diagnostic decision support systems. RESULTS: We propose two new algorithms, LOADDx and SCADDx, to combine a patient's gene expression data with gene-disease association and other related information available in the form of a KB, to assist personalized disease diagnosis. We have tested both of the algorithms on two KBs and on four real-world gene expression datasets of respiratory viral infection caused by Influenza-like viruses of 19 subtypes. We also compare the performance of proposed algorithms with that of five existing state-of-the-art machine learning algorithms (k-NN, Random Forest, XGBoost, Linear SVM, and SVM with RBF Kernel) using two validation approaches: LOOCV and a single internal validation set. Both SCADDx and LOADDx outperform the existing algorithms when evaluated with both validation approaches. SCADDx is able to detect infections with up to 100% accuracy in the cases of Datasets 2 and 3. Overall, SCADDx and LOADDx are able to detect an infection within 72 h of infection with 91.38% and 92.66% average accuracy respectively considering all four datasets, whereas XGBoost, which performed best among the existing machine learning algorithms, can detect the infection with only 86.43% accuracy on an average. CONCLUSIONS: We demonstrate how our novel idea of using the most and least differentially expressed genes in combination with a KB can enable identification of the diseases that a patient is most likely to have at a particular time, from a KB with thousands of diseases. Moreover, the proposed algorithms can provide a short ranked list of the most likely diseases for each patient along with their most affected genes, and other entities linked with them in the KB, which can support health care professionals in their decision-making.

Development and assessment of the performance of a shared ventilatory system that uses clinically available components to individualize tidal volumes.

OBJECTIVES: To develop and assess a system for shared ventilation using clinically available components to individualize tidal volumes. DESIGN: Evaluation and in vitro validation study SETTING: Ventilator shortage during the SARS-CoV-2 pandemic. PARTICIPANTS: The team consisted of physicians, bioengineers, computer programmers, and medical technology professionals. METHODS: Using clinically available components, a system of ventilation consisting of two ventilatory limbs was assembled and connected to a ventilator. Monitors for each limb were developed using open-source software. Firstly, the effect of altering ventilator settings on tidal volumes delivered to each limb was determined. Secondly, the impact of altering the compliance and resistance of one limb on the tidal volumes delivered to both limbs was analysed. Experiments were repeated three times to determine system variability. RESULTS: The system permitted accurate and reproducible titration of tidal volumes to each limb over a range of ventilator settings and simulated lung conditions. Alteration of ventilator inspiratory pressures, of respiratory rates, and I:E ratio resulted in very similar tidal volumes delivered to each limb. Alteration of compliance and resistance in one limb resulted in reproducible alterations in tidal volume to that test lung, with little change to tidal volumes in the other lung. All tidal volumes delivered were reproducible. CONCLUSIONS: We demonstrate the reliability of a shared ventilation system assembled using commonly available clinical components that allows titration of individual tidal volumes. This system may be useful as a strategy of last resort for Covid-19, or other mass casualty situations, where the need for ventilators exceeds supply.

E-Cigarette Liquids and Aldehyde Flavoring Agents Inhibit CYP2A6 Activity in Lung Epithelial Cells.

Certain e-liquids and aromatic aldehyde flavoring agents were previously identified as inhibitors of microsomal recombinant CYP2A6, the primary nicotine-metabolizing enzyme. However, due to their reactive nature, aldehydes may react with cellular components before reaching CYP2A6 in the endoplasmic reticulum. To determine whether e-liquid flavoring agents inhibited CYP2A6 in a cellular system, we investigated their effects on CYP2A6 using BEAS-2B cells transduced to overexpress CYP2A6. We demonstrated that two e-liquids and three aldehyde flavoring agents (cinnamaldehyde, benzaldehyde, and ethyl vanillin) exhibited dose-dependent inhibition of cellular CYP2A6.

Biosynthetic Enzyme-guided Disease Correlation Connects Gut Microbial Metabolites Sulfonolipids to Inflammatory Bowel Disease Involving TLR4 Signaling.

The trillions of microorganisms inhabiting the human gut are intricately linked to human health. At the species abundance level, correlational studies have connected specific bacterial taxa to various diseases. While the abundances of these bacteria in the gut serve as good indicators for disease progression, understanding the functional metabolites they produce is critical to decipher how these microbes influence human health. Here, we report a unique biosynthetic enzyme-guided disease correlation approach to uncover microbial functional metabolites as potential molecular mechanisms in human health. We directly connect the expression of gut microbial sulfonolipid (SoL) biosynthetic enzymes to inflammatory bowel disease (IBD) in patients, revealing a negative correlation. This correlation is then corroborated by targeted metabolomics, identifying that SoLs abundance is significantly decreased in IBD patient samples. We experimentally validate our analysis in a mouse model of IBD, showing that SoLs production is indeed decreased while inflammatory markers are increased in diseased mice. In support of this connection, we apply bioactive molecular networking to show that SoLs consistently contribute to the immunoregulatory activity of SoL-producing human microbes. We further reveal that sulfobacins A and B, two representative SoLs, primarily target Toll-like receptor 4 (TLR4) to mediate immunomodulatory activity through blocking TLR4's natural ligand lipopolysaccharide (LPS) binding to myeloid differentiation factor 2, leading to significant suppression of LPS-induced inflammation and macrophage M1 polarization. Together, these results suggest that SoLs mediate a protective effect against IBD through TLR4 signaling and showcase a widely applicable biosynthetic enzyme-guided disease correlation approach to directly link the biosynthesis of gut microbial functional metabolites to human health.

Dynamic Bayesian Network Learning to Infer Sparse Models From Time Series Gene Expression Data.

One of the key challenges in systems biology is to derive gene regulatory networks (GRNs) from complex high-dimensional sparse data. Bayesian networks (BNs) and dynamic Bayesian networks (DBNs) have been widely applied to infer GRNs from gene expression data. GRNs are typically sparse but traditional approaches of BN structure learning to elucidate GRNs often produce many spurious (false positive) edges. We present two new BN scoring functions, which are extensions to the Bayesian Information Criterion (BIC) score, with additional penalty terms and use them in conjunction with DBN structure search methods to find a graph structure that maximises the proposed scores. Our BN scoring functions offer better solutions for inferring networks with fewer spurious edges compared to the BIC score. The proposed methods are evaluated extensively on auto regressive and DREAM4 benchmarks. We found that they significantly improve the precision of the learned graphs, relative to the BIC score. The proposed methods are also evaluated on three real time series gene expression datasets. The results demonstrate that our algorithms are able to learn sparse graphs from high-dimensional time series data. The implementation of these algorithms is open source and is available in form of an R package on GitHub at https://github.com/HamdaBinteAjmal/DBN4GRN, along with the documentation and tutorials.

Exhaled breath condensate biomarkers in critically ill, mechanically ventilated patients.

Pneumonia is a significant risk for critically ill, mechanically ventilated (CIMV) patients. Diagnosis of pneumonia generally requires a combination of clinician-guided diagnoses and clinical scoring systems. Exhaled breath condensate (EBC) can be safely collected non-invasively from CIMV patients. Hundreds of biomarkers in EBC are associated with acute disease states, including pneumonia. We evaluated cytokines in EBC from CIMV patients and hypothesized that these biomarkers would correlate with disease severity in pneumonia, sepsis, and death. EBC IL-2 levels were associated with chest radiograph severity scores (odds ratio = 1.68; 95% confidence interval = 1.09-2.60; P = 0.02). EBC TNF-α levels were also associated with pneumonia (odds ratio = 3.20; 95% confidence interval = 1.19-8.65; P = 0.02). The techniques and results from this study may be useful for all mechanically ventilated patients.

Ozone Reacts With Carbon Black to Produce a Fulvic Acid-Like Substance and Increase an Inflammatory Effect.

Exposure to ambient ozone has been associated with increased human mortality. Ozone exposure can introduce oxygen-containing functional groups in particulate matter (PM) effecting a greater capacity of the particle for metal complexation and inflammatory effect. We tested the postulate that (1) a fulvic acid-like substance can be produced through a reaction of a carbonaceous particle with high concentrations of ozone and (2) such a fulvic acid-like substance included in the PM can initiate inflammatory effects following exposure of respiratory epithelial (BEAS-2B) cells and an animal model (male Wistar Kyoto rats). Carbon black (CB) was exposed for 72 hours to either filtered air (CB-Air) or approximately 100 ppm ozone (CB-O3). Carbon black exposure to high levels of ozone produced water-soluble, fluorescent organic material. Iron import by BEAS-2B cells at 4 and 24 hours was not induced by incubations with CB-Air but was increased following coexposures of CB-O3 with ferric ammonium citrate. In contrast to CB-Air, exposure of BEAS-2B cells and rats to CB-O3 for 24 hours increased expression of pro-inflammatory cytokines and lung injury, respectively. It is concluded that inflammatory effects of carbonaceous particles on cells can potentially result from (1) an inclusion of a fulvic acid-like substance after reaction with ozone and (2) changes in iron homeostasis following such exposure.

Oleic acid and derivatives affect human endothelial cell mitochondrial function and vasoactive mediator production.

BACKGROUND: Inhalation of common air pollutants such as diesel and biodiesel combustion products can induce vascular changes in humans which may contribute to increased mortality and morbidity associated with fine particulate matter exposures. Diesel, biodiesel, and other combustion byproducts contain fatty acid components capable of entering the body through particulate matter inhalation. Fatty acids can also be endogenously released into circulation following a systemic stress response to some inhaled pollutants such as ozone. When in the circulation, bioactive fatty acids may interact with cells lining the blood vessels, potentially inducing endothelial dysfunction. To examine whether fatty acids could potentially be involved in human vascular responses to air pollutants, we determined the effects of fatty acids and derivatives on important vascular cell functions. METHODS: Human umbilical vein endothelial cells (HUVEC) were exposed in vitro to oleic acid (OA) or OA metabolites for 4-48 h. Cytotoxicity, vasodilator production (by ELISA measurement), mitochondrial function (using Sea Horse assays), and iron metabolism (inferred by ICP-OES measurements) were examined, with standard statistical testing (ANOVA, t-tests) employed. RESULTS: Dose-dependent cytotoxicity was noted at 24 h, with 12-hydroxy OA more potent than OA. Mitochondrial stress testing showed that 12-hydroxy OA and OA induce mitochondrial dysfunction. Analysis of soluble mediator release from HUVEC showed a dose-dependent increase in prostaglandin F2α, a lipid involved in control of vascular tone, at 24 h (85% above controls) after OA-BSA exposure. RT-PCR analysis revealed OA did not induce changes in gene expression at noncytotoxic concentrations in exposed HUVEC, but 12-OH OA did alter ICAM and COX2 gene expression. CONCLUSIONS: Together, these data demonstrate that FA may be capable of inducing cytotoxic effects and altering expression of mediators of vascular function following inhalation exposure, and may be implicated in air pollutant-induced deaths and hospitalizations. (267 of max 350 words).

Impact of E-Cigarette Liquid Flavoring Agents on Activity of Microsomal Recombinant CYP2A6, the Primary Nicotine-Metabolizing Enzyme.

Nicotine is the primary psychoactive chemical in both traditional and electronic cigarettes (e-cigarettes). Nicotine levels in both traditional cigarettes and e-cigarettes are an important concern for public health. Nicotine exposure due to e-cigarette use is of importance primarily due to the addictive potential of nicotine, but there is also concern for nicotine poisoning in e-cigarette users. Nicotine concentrations in e-liquids vary widely. Additionally, there is significant genetic variability in the rate of metabolism of nicotine due to polymorphisms of CYP2A6, the enzyme responsible for the metabolism of approximately 80% of nicotine. Recent studies have shown CYP2A6 activity is also reduced by aromatic aldehydes such as those added to e-liquids as flavoring agents, which may increase nicotine serum concentrations. However, the impacts of flavored e-liquids on CYP2A6 activity are unknown. In this study, we investigated the impact of three flavored e-liquids on microsomal recombinant CYP2A6. Microsomal recombinant CYP2A6 was challenged at e-liquid concentrations ranging up to 0.125% (v/v) and monitored for metabolic activity using a probe molecule approach. Two e-liquids exhibited dose-dependent inhibition of CYP2A6 activity. Mass spectrometry was conducted to identify flavoring agents in flavored e-liquids that inhibited CYP2A6. Microsomal recombinant CYP2A6 was subsequently exposed to flavoring agents at concentrations ranging from 0.03 µM to 500 µM. Cinnamaldehyde and benzaldehyde were found to be the most potent inhibitors of microsomal CYP2A6 of the flavoring agents tested, with identified IC50 values of 1.1 µM and 3.0 µM, respectively. These data indicate certain aromatic aldehyde flavoring agents are potent inhibitors of CYP2A6, which may reduce nicotine metabolism in vivo. These findings indicate an urgent need to evaluate the effects of flavoring agents in e-cigarette liquids on the pharmacokinetics of nicotine in vivo.

Robust Classification of High-Dimensional Spectroscopy Data Using Deep Learning and Data Synthesis.

This paper presents a new approach to classification of high-dimensional spectroscopy data and demonstrates that it outperforms other current state-of-the art approaches. The specific task we consider is identifying whether samples contain chlorinated solvents or not, based on their Raman spectra. We also examine robustness to classification of outlier samples that are not represented in the training set (negative outliers). A novel application of a locally connected neural network (NN) for the binary classification of spectroscopy data is proposed and demonstrated to yield improved accuracy over traditionally popular algorithms. Additionally, we present the ability to further increase the accuracy of the locally connected NN algorithm through the use of synthetic training spectra, and we investigate the use of autoencoder based one-class classifiers and outlier detectors. Finally, a two-step classification process is presented as an alternative to the binary and one-class classification paradigms. This process combines the locally connected NN classifier, the use of synthetic training data, and an autoencoder based outlier detector to produce a model which is shown to both produce high classification accuracy and be robust in the presence of negative outliers.

A Fulvic Acid-like Substance Participates in the Pro-inflammatory Effects of Cigarette Smoke and Wood Smoke Particles.

We tested the postulates that (1) a fulvic acid (FA)-like substance is included in cigarette smoke and wood smoke particles (WSP) and (2) cell exposure to this substance results in a disruption of iron homeostasis, associated with a deficiency of the metal and an inflammatory response. The fluorescence excitation-emission matrix spectra of the water-soluble components of cigarette smoke condensate and WSP (Cig-WS and Wood-WS) approximated those for the standard reference materials, Suwanee River and Nordic fulvic acids (SRFA and NFA). Fourier transform infrared spectra for the FA fraction of cigarette smoke and WSP (Cig-FA and Wood-FA), SRFA, and NFA also revealed significant similarities (O-H bond in alcohols, phenols, and carboxylates, C═O in ketones, aldehydes, and carboxylates, and a significant carboxylate content). After exposure to Cig-WS and Wood-WS and the FA standards, iron was imported by respiratory epithelial cells, reflecting a functional iron deficiency. The release of pro-inflammatory mediators interleukin (IL)-8 and IL-6 by respiratory epithelial cells also increased following exposures to Cig-WS, Wood-WS, SRFA, and NFA. Co-exposure of the respiratory epithelial cells with iron decreased supernatant concentrations of the ILs relative to exposures to Cig-WS, Wood-WS, SRFA, and NFA alone. It is concluded that (1) a FA-like substance is included in cigarette smoke and WSP and (2) respiratory epithelial cell exposure to this substance results in a disruption of iron homeostasis associated with both a cell deficiency of the metal and an inflammatory response.

Air pollutants disrupt iron homeostasis to impact oxidant generation, biological effects, and tissue injury.

Air pollutants cause changes in iron homeostasis through: 1) a capacity of the pollutant, or a metabolite(s), to complex/chelate iron from pivotal sites in the cell or 2) an ability of the pollutant to displace iron from pivotal sites in the cell. Through either pathway of disruption in iron homeostasis, metal previously employed in essential cell processes is sequestered after air pollutant exposure. An absolute or functional cell iron deficiency results. If enough iron is lost or is otherwise not available within the cell, cell death ensues. However, prior to death, exposed cells will attempt to reverse the loss of requisite metal. This response of the cell includes increased expression of metal importers (e.g. divalent metal transporter 1). Oxidant generation after exposure to air pollutants includes superoxide production which functions in ferrireduction necessary for cell iron import. Activation of kinases and phosphatases and transcription factors and increased release of pro-inflammatory mediators also result from a cell iron deficiency, absolute or functional, after exposure to air pollutants. Finally, air pollutant exposure culminates in the development of inflammation and fibrosis which is a tissue response to the iron deficiency challenging cell survival. Following the response of increased expression of importers and ferrireduction, activation of kinases and phosphatases and transcription factors, release of pro-inflammatory mediators, and inflammation and fibrosis, cell iron is altered, and a new metal homeostasis is established. This new metal homeostasis includes increased total iron concentrations in cells with metal now at levels sufficient to meet requirements for continued function.

Trends in Primary Proximal Interphalangeal Joint System and Revisions for Osteoarthritis of the Hand in the Medicare Database.

Background: Proximal interphalangeal arthroplasty (PIPA) has been indicated for patients suffering from osteoarthritis (OA) or rheumatoid arthritis of the hand. Although there is extensive literature showing the outcomes of PIPA, there is paucity in the literature regarding trends of PIPA in patients with OA of the hand. The purpose of this study was to determine annual primary utilization and revision PIPA trends within the Medicare population with the use of an administrative database. Methods: A retrospective query was performed using the Medicare Standard Analytical Files from the PearlDiver database. Patients undergoing primary and revision PIPA with hand OA were queried using International Classification of Disease, Ninth Revision, and Current Procedural Terminology coding. Primary outcomes analyzed included annual and revision utilization of PIPA and demographic comparison of age, gender, and geographic location. Statistical analysis was primarily descriptive. An α value less than 0.05 was considered statistically significant. Results: The query returned 10 191 patients who underwent primary and revision PIPA between 2005 and 2013. Calculated annual growth rate for primary and revision PIPA was 2.40% and -0.03%, respectively (P < .001). Patients between the ages of 70 and 74 years represented most of the patients undergoing a primary PIPA, whereas patients between 65 and 69 years most commonly underwent a revision procedure. Regionally, primary and revision PIPA were most commonly performed in the South. Conclusion: The data demonstrate an increased use of primary PIPA utilization for patients with OA, whereas revision PIPA decreased. The increased use indicates the increasing demand for PIPA in the United States.

How do cancer-sniffing dogs sort biological samples? Exploring case-control samples with non-targeted LC-Orbitrap, GC-MS, and immunochemistry methods.

Early identification of disease onset is regarded as an important factor for successful medical intervention. However, cancer and other long-term latency diseases are rare and may take years to manifest clinically. As such, there are no gold standards with which to immediately validate proposed preclinical screening methodologies. There is evidence that dogs can sort samples reproducibly into yes/no categories based on case-control training, but the basis of their decisions is unknown. Because dogs are sniffing air, the distinguishing chemicals must be either in the gas-phase or attached to aerosols and/or airborne particles. Recent biomonitoring research has shown how to extract and analyze semi- and non-volatile compounds from human breath in exhaled condensates and aerosols. Further research has shown that exhaled aerosols can be directly collected on standard hospital-style olefin polypropylene masks and that these masks can be used as a simple sampling scheme for canine screening. In this article, detailed liquid chromatography-high resolution mass spectrometry (LC-HR-MS) with Orbitrap instrumentation and gas chromatography-mass spectrometry (GC-MS) analyses were performed on two sets of masks sorted by consensus of a four-dog cohort as either cancer or control. Specifically, after sorting by the dogs, sample masks were cut into multiple sections and extracted for LC-MS and GC-MS non-targeted analyses. Extracts were also analyzed for human cytokines, confirming the presence of human aerosol content above levels in blank masks. In preliminary evaluations, 345 and 44 high quality chemical features were detected by LC-MS and GC-MS analyses, respectively. These features were used to develop provisional orthogonal projection to latent structures-discriminant analysis (OPLS-DA) models to determine if the samples classified as cancer (case) or non-cancer (control) by the dogs could be separated into the same groups using analytical instrumentation. While the OPLS-DA model for the LC-HR-MS data was able to separate the two groups with statistical significance, although weak explanatory power, the GC-MS model was not found to be significant. These results suggest that the dogs may rely on the less volatile compounds from breath aerosol that were analyzed by LC-HR-MS than the more volatile compounds observed by GC-MS to sort mask samples into groups. These results provide justification for more expansive studies in the future that aim to characterize specific chemical features, and the role(s) of these features in maintaining homeostatic biological processes.

Quartz Disrupts Iron Homeostasis in Alveolar Macrophages To Impact a Pro-Inflammatory Effect.

The biological response of bronchial epithelial cells to particles is associated with a sequestration of cell metal by the particle surface and a subsequent disruption in host iron homeostasis. The macrophage is the cell type resident in the respiratory tract that is most likely to make initial contact with inhaled particles. We tested the postulates that (1) silica, a prototypical particle, disrupts iron homeostasis in alveolar macrophages (AMs); and (2) the altered iron homeostasis results in both an oxidative stress and pro-inflammatory effects. Human AMs (1.0 × 106/mL) demonstrated an increased import of iron following particle exposure with nonheme iron concentrations of 0.57 ± 0.03, 1.72 ± 0.09, 0.88 ± 0.09, and 3.21 ± 0.11 ppm in cells exposed for 4 h to media, 500 µM ferric ammonium citrate (FAC), 100 µg/mL silica, and both silica and FAC, respectively. Intracellular ferritin concentrations and iron release were similarly increased after AM exposure to FAC and silica. Silica increased oxidant generation by AMs measured using both dichlorofluorescein diacetate fluorescence and reduction of nitroblue tetrazolium salt. Concentrations of interleukin (IL)-1ß, IL-6, IL-8, and tumor necrosis factor-α in macrophage supernatant increased following 100 µg/mL silica exposure for 24 h. Treatment of AMs with 500 µM FAC decreased both oxidant generation and cytokine release associated with silica exposure, supporting a dependence of these effects on sequestration of cell metal by the particle surface. We conclude that (1) silica exposure disrupts iron homeostasis resulting in increased import, accumulation, and release of the metal; and (2) the altered iron homeostasis following silica exposure impacts oxidant generation and pro-inflammatory effects.

Perioperative complications in patients with sleep apnea following primary total shoulder arthroplasty: An analysis of 33,366 patients.

INTRODUCTION: The study evaluated whether sleep apnea (SA) patients undergoing total shoulder arthroplasty (TSA) are at greater odds of: 1) medical complications; 2) implant-related complications; 3) readmission rates; and 4) costs. METHODS: Complications and readmissions were assessed using logistic regression analysis. Welch's t-test was used to compare CCI and cost between cohorts. RESULTS: 33,366 patients equally distributed in both cohorts. SA increased the odds of medical [Odds-ratio (OR)]: 2.52, p < 0.001) and implant-related complications (OR: 1.43, p < 0.001). Readmission rates were similar to controls (OR: 0.99, p = 0.878), whereas costs were higher (p < 0.001). CONCLUSION: SA increases complications and costs following TSA.