A Novel Lactic Acid Bacteria Mixture: Macrophage-Targeted Prophylactic Intervention in Colorectal Cancer Management

Colorectal cancer (CRC) is one of the most common forms of cancer. Its onset from chronic inflammation is widely accepted. Moreover, dysbiosis plays an undeniable role, thus the use of probiotics in CRC has been suggested. They exhibit both anti- and pro-inflammatory properties and restore balance in the microbiota. The aim of this study was to investigate the immunomodulatory properties of six lactobacilli with probiotic features in an in vitro model of macrophage-like cells and to test these pooled probiotics for their anti-tumour properties in a chemically induced CRC model using Wistar male rats. Upon co-culture of M1- and M2-like macrophages with lactobacilli, cytokine release (TNF-α, IL-1β, IL-18, IL-23) and phagocytic activity using fluorescent-labelled bacteria were tested. The effects of orally administered probiotics on basic cancer and immune parameters and cytokine concentration (TNF-α, IL-1β, IL-18) in colon tumours were studied. Tested lactobacilli exhibited both pro- and anti-inflammatory properties in in vitro conditions. In vivo study showed that the administration of probiotics was able to decrease multiplicity, volume and total tumour numbers, restore colon length (p &lt; 0.05) and increase IL-18 production (p &lt; 0.05) in tumour tissue. These data indicate both an immunomodulatory effect of probiotics on distinct macrophage subsets and a protective effect against chemically-induced CRC.</jats:p

Plasma Properties in the Plume of a Hall Thruster Cluster

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76225/1/AIAA-3765-486.pd

Effects of Cathode Configuration on Hall Thruster Cluster Plume Properties

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76620/1/AIAA-24636-518.pd

Can we estimate the impact of small targeted dietary changes on human health and environmental sustainability?

A recent analysis by Stylianou et al. (2021) estimated the impact of small dietary changes in the consumption of individual foods on human health and the environment, expressed as minutes of healthy life lost or gained daily combined with dietary carbon footprints. While an appealing concept given its simplistic interpretation, we aim to draw the attention of nLCA practitioners and developers to the significant limitations and uncertainties of this analysis, based on existing evidence. Stylianou's approach produces results that fail to recognize the importance of essential nutrient density and the risks associated with ultra-processed foods, added sugar, and refined starches. The novel impact assessment undoubtedly brings a new perspective to the growing field of nutritional Life Cycle Assessment. However, the authors neglect numerous methodological limitations, fail to direct the readers' attention to (mis)interpretation risks, and draw highly definitive recommendations aiming to directly influence consumer choices and policymaking. Due to extensive data limitations and associated uncertainties in extant databases (both environmental and nutritional), we recommend caution in the use of this (or any other) food classification system to inform consumer behavior, front-of-package labelling, policies, and programs

Universality in Heavy Fermions Revisited

A previous scaling analysis of pressure experiments in heavy fermion is reviewed and enlarged. We show that the critical exponents obtained from this analysis indicate that a one-parameter scaling describes these experiments. We obtain explicitly the enhancemente factors showing that these systems are indeed near criticality and that the scaling approach is appropriate. The physics responsible for the one-parameter scaling and breakdown of hyperscaling is clarified. We discuss a microsocopic theory that is in agreement with the experiments. The scaling theory is generalized for the case the shift and crossover exponents are different. The exponents governing the physical behavior along the non-Fermi liquid trajectory are obtained for this case.Comment: 7 pages, Latex, 3 Postscript figures, to be published in Physical Review

Performance Characteristics of a Cluster of 5-kW Laboratory Hall Thrusters

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76117/1/AIAA-19752-159.pd

Effect of magnetic and non-magnetic impurities on highly anisotropic superconductivity

We generalize Abrikosov-Gor'kov solution of the problem of weakly coupled superconductor with impurities on the case of a multiband superconductor with arbitrary interband order parameter anisotropy, including interband sign reversal of the order parameter. The solution is given in terms of the effective (renormalized) coupling matrix and describes not only $T_c$ suppression but also renormalization of the superconducting gap basically at all temperatures. In many limiting cases we find analytical solutions for the critical temperature suppression. We illustrate our results by numerical calculations for two-band model systems.Comment: 18 pages (12pt) RevTeX, 4 postscript figure

Coexistence of Singlet and Triplet Attractive Channels in the Pairing Interactions Mediated by Antiferromagnetic Fluctuations

We propose a phase diagram of quasi-low-dimensional type II superconductors in parallel magnetic fields, when antiferromagnetic fluctuations contribute to the pairing interactions. We point out that pairing interactions mediated by antiferromagnetic fluctuations necessarily include both singlet channels and triplet channels as attractive interactions. Usually, a singlet pairing is favored at zero field, but a triplet pairing occurs at high fields where the singlet pairing is suppressed by the Pauli paramagnetic pair-breaking effect. As a result, the critical field increases divergently at low temperatures. A possible relation to experimental phase diagrams of a quasi-one-dimensional organic superconductor is briefly discussed. We also discuss a possibility that a triplet superconductivity is observed even at zero field.Comment: 4 pages, 1 figure (Latex, revtex.sty, epsf.sty

Comparing families of dynamic causal models

Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and then makes inferences based on the parameters of that model. This “best model” approach is very useful but can become brittle if there are a large number of models to compare, and if different subjects use different models. To overcome this shortcoming we propose the combination of two further approaches: (i) family level inference and (ii) Bayesian model averaging within families. Family level inference removes uncertainty about aspects of model structure other than the characteristic of interest. For example: What are the inputs to the system? Is processing serial or parallel? Is it linear or nonlinear? Is it mediated by a single, crucial connection? We apply Bayesian model averaging within families to provide inferences about parameters that are independent of further assumptions about model structure. We illustrate the methods using Dynamic Causal Models of brain imaging data