Breath Hydrogen Gas Concentration Linked to Intestinal Gas Distribution and Malabsorption in Patients with Small-bowel Pseudo-obstruction

Background: The patient with colonic obstruction may frequently have bacterial overgrowth and increased breath hydrogen (H2) levels because the bacterium can contact with food residues for longer time. We experienced two cases with intestinal obstruction whose breath H2 concentrations were measured continuously.Case 1: A 70-year-old woman with small bowel obstruction was treated with a gastric tube. When small bowel gas decreased and colonic gas was demonstrated on the plain abdominal radiograph, the breath H2 concentration increased to 6 ppm and reduced again shortly.Case 2: A 41-year-old man with functional small bowel obstruction after surgical treatment was treated with intravenous administration of erythromycin. Although the plain abdominal radiograph demonstrated a decrease of small-bowel gas, the breath H2 gas kept the low level. After a clear-liquid meal was supplied, fasting breath H2 concentration increased rapidly to 22 ppm and gradually decreased to 9 ppm despite the fact that the intestinal gas was unchanged on X-ray. A rapid increase of breath H2 concentration may reflect the movement of small bowel contents to the colon in patients with small-bowel pseudo-obstruction or malabsorption following diet progression.Conclusions: Change in breath H2 concentration had a close association with distribution and movement of intestinal gas

Biomaker CA: a Biome Maker project using Cellular Automata

We introduce Biomaker CA: a Biome Maker project using Cellular Automata (CA). In Biomaker CA, morphogenesis is a first class citizen and small seeds need to grow into plant-like organisms to survive in a nutrient starved environment and eventually reproduce with variation so that a biome survives for long timelines. We simulate complex biomes by means of CA rules in 2D grids and parallelize all of its computation on GPUs through the Python JAX framework. We show how this project allows for several different kinds of environments and laws of 'physics', alongside different model architectures and mutation strategies. We further analyze some configurations to show how plant agents can grow, survive, reproduce, and evolve, forming stable and unstable biomes. We then demonstrate how one can meta-evolve models to survive in a harsh environment either through end-to-end meta-evolution or by a more surgical and efficient approach, called Petri dish meta-evolution. Finally, we show how to perform interactive evolution, where the user decides how to evolve a plant model interactively and then deploys it in a larger environment. We open source Biomaker CA at: https://tinyurl.com/2x8yu34s .Comment: 20 pages, 23 figures. For code base, see https://tinyurl.com/2x8yu34

Effect of Paraquat Herbicide on Oxidative Stress Biomaker Enzyme Activities in C. Gariepinus

Toxicity assessment was conducted for 96hr exposure duration using synthetic herbicide (paraquat dichloride 276g/L) on Claris gariepinus with mean weight range of 27.2 - 29.7g and mean length 10.95 -15.5cm. They were exposed to varying herbicide concentrations of 0.0, 3.45, 6.90, 10.35 and 13.5mg/L with 5-levels exposure concentrations in a Completely Randomized Design (CRD). Liver, gills and kidney tissues were analyzed for oxidative stress enzymes activities using Solarbio science assay kit (BC1170, 0170 and 0020). Four days lethal concentration (LC50) value for 96hr was found to be 7.298mg/L. The treated fish displayed erratic swimming with irregular opercular movement, loss of reflex, mucus secretion and increased air gulping with the increasing concentration of the herbicide compared with the control fish. Antioxidant biomarkers activities revealed that Glutathione S-transferase (GST), catalase (CAT) and superoxide dismutase (SOD) activities increased significantly (P<0.05) in the gills, liver and kidney tissues at higher concentrations compared with control. It can be deduced that alterations in the oxidative stress enzyme activities in the exposed fish to paraquat exert toxic effect on the liver, gills and kidney tissues. It is therefore recommended that appropriate authorities should develop strategies on minimizing the indiscriminate use of synthetic herbicides due to their impact on aquatic biota such as fish in order to reduce its potential risk to other non-target organisms. Keywords: Clarias gariepinus, Lethal concentration, Oxidative Stress enzymes, Paraquat, Toxicity assessmen

3D-Printable and Enzymatically Active Composite Materials Based on Hydrogel-Filled High Internal Phase Emulsions

The immobilization of enzymes in biocatalytic flow reactors is a common strategy to increase enzyme reusability and improve biocatalytic performance. Extrusion-based 3D bioprinting has recently emerged as a versatile tool for the fabrication of perfusable hydrogel grids containing entrapped enzymes for the use in such reactors. This study demonstrates the suitability of water-in-oil high internal phase emulsions (HIPEs) as 3D-printable bioinks for the fabrication of composite materials with a porous polymeric scaffold (polyHIPE) filled with enzyme-laden hydrogel. The prepared HIPEs exhibited excellent printability and are shown to be suitable for the printing of complex three-dimensional structures without the need for sacrificial support material. An automated activity assay method for the systematic screening of different material compositions in small-scale batch experiments is presented. The monomer mass fraction in the aqueous phase and the thickness of printed objects were found to be the most important parameters determining the apparent activity of the immobilized enzyme. Mass transfer limitations and enzyme inactivation were identified as probable factors reducing the apparent activity. The presented HIPE-based bioinks enable the fabrication of flow-optimized and more efficient biocatalytic reactors while the automated activity assay method allows the rapid screening of materials to optimize the biocatalytic efficiency further without time-consuming flow-through experiments involving whole printed reactors

Revealing metabolite biomarkers for acupuncture treatment by linear programming based feature selection

BACKGROUND: Acupuncture has been practiced in China for thousands of years as part of the Traditional Chinese Medicine (TCM) and has gradually accepted in western countries as an alternative or complementary treatment. However, the underlying mechanism of acupuncture, especially whether there exists any difference between varies acupoints, remains largely unknown, which hinders its widespread use. RESULTS: In this study, we develop a novel Linear Programming based Feature Selection method (LPFS) to understand the mechanism of acupuncture effect, at molecular level, by revealing the metabolite biomarkers for acupuncture treatment. Specifically, we generate and investigate the high-throughput metabolic profiles of acupuncture treatment at several acupoints in human. To select the subsets of metabolites that best characterize the acupuncture effect for each meridian point, an optimization model is proposed to identify biomarkers from high-dimensional metabolic data from case and control samples. Importantly, we use nearest centroid as the prototype to simultaneously minimize the number of selected features and the leave-one-out cross validation error of classifier. We compared the performance of LPFS to several state-of-the-art methods, such as SVM recursive feature elimination (SVM-RFE) and sparse multinomial logistic regression approach (SMLR). We find that our LPFS method tends to reveal a small set of metabolites with small standard deviation and large shifts, which exactly serves our requirement for good biomarker. Biologically, several metabolite biomarkers for acupuncture treatment are revealed and serve as the candidates for further mechanism investigation. Also biomakers derived from five meridian points, Zusanli (ST36), Liangmen (ST21), Juliao (ST3), Yanglingquan (GB34), and Weizhong (BL40), are compared for their similarity and difference, which provide evidence for the specificity of acupoints. CONCLUSIONS: Our result demonstrates that metabolic profiling might be a promising method to investigate the molecular mechanism of acupuncture. Comparing with other existing methods, LPFS shows better performance to select a small set of key molecules. In addition, LPFS is a general methodology and can be applied to other high-dimensional data analysis, for example cancer genomics