Adrenergic/Cholinergic Immunomodulation in the Rat Model—In Vivo Veritas?

For several years, our group has been studying the in vivo role of adrenergic and cholinergic mechanisms in the immune-neuroendocrine dialogue in the rat model. The main results of these studies can be summarized as follows: (1) exogenous or endogenous catecholamines suppress PBL functions through alpha-2-receptor-mediated mechanisms, lymphocytes of the spleen are resistant to adrenergic in vivo stimulation, (2) direct or indirect cholinergic treatment leads to enhanced ex vivo functions of splenic and thymic lymphocytes leaving PBL unaffected, (3) cholinergic pathways play a critical role in the “talking back” of the immune system to the brain, (4) acetylcholine inhibits apoptosis of thymocytes possibly via direct effects on thymic epithelial cells, and may thereby influence T-cell maturation, (5) lymphocytes of the various immunological compartments were found to be equipped with the key enzymes for the synthesis of both acetylcholine and norepinephrine, and to secrete these neurotransmitters in culture supernatant

Markov entropy decomposition: a variational dual for quantum belief propagation

We present a lower bound for the free energy of a quantum many-body system at finite temperature. This lower bound is expressed as a convex optimization problem with linear constraints, and is derived using strong subadditivity of von Neumann entropy and a relaxation of the consistency condition of local density operators. The dual to this minimization problem leads to a set of quantum belief propagation equations, thus providing a firm theoretical foundation to that approach. The minimization problem is numerically tractable, and we find good agreement with quantum Monte Carlo for the spin-half Heisenberg anti-ferromagnet in two dimensions. This lower bound complements other variational upper bounds. We discuss applications to Hamiltonian complexity theory and give a generalization of the structure theorem of Hayden, Jozsa, Petz and Winter to trees in an appendix

Towards Emotion Recognition: A Persistent Entropy Application

Emotion recognition and classification is a very active area of research. In this paper, we present a first approach to emotion classification using persistent entropy and support vector machines. A topology-based model is applied to obtain a single real number from each raw signal. These data are used as input of a support vector machine to classify signals into 8 different emotions (calm, happy, sad, angry, fearful, disgust and surprised)

Estrogen-Receptor Expression and Function in Thymocytes in Relation to Gender and Age

The expression of estrogen receptor (ER) in thymocytes was studied in young, middle-aged, and old (2, 12, and 24 months, respectively) female and male C57BL/6J mice. Western immunoblots prepared from the thymocytes of females of all age groups showed the presence of a 67-kD protein band, which has been associated with the apparent MW of denatured ER. Flow cytometry analysis o,f cells stained with a monoclonal anti-ER antibody (clone 13H2) disclosed ER expression in both females and males of all age groups. In vivo treatment with estradiol (E2) led to an increase in the specific activity of thymic creatine kinase (CK) in the female mice, whereas the male thymocytes responded with an increase in CK activity only on treatment with dihydrotestosterone (DHT). The data show no differences in ER expression between male and females, but the receptor appears not to be functional in males. Interestingly, when estradiol was applied to co-cultures of lymphoid-depleted fetal thymus (FT) explants and bone-marrow cells, or thymocytes, from young and old females, it resulted in increased cellularity of cultures containing cells of the young, and not those of the old. The proportion of CD4/CD8 phenotypes of the developing cells in these cultures was not affected by E2 treatment. These observations provide a new insight into ER expression and function in T-cell development in relation to gender and age

Supervised Human-Guided Data Exploration

Peer reviewe

Robustness and Generalization

We derive generalization bounds for learning algorithms based on their robustness: the property that if a testing sample is "similar" to a training sample, then the testing error is close to the training error. This provides a novel approach, different from the complexity or stability arguments, to study generalization of learning algorithms. We further show that a weak notion of robustness is both sufficient and necessary for generalizability, which implies that robustness is a fundamental property for learning algorithms to work

Moderate exercise may attenuate some aspects of immunosenescence

BACKGROUND: Immunosenescence is related to the deterioration of many immune functions, which may be manifested in increased susceptibility to infection, cancer, and autoimmunity. Lifestyle factors, such as diet or physical activity, may influence the senescence of the immune system. It is widely accepted that moderate physical activity may cause beneficial effects for physical and psychological health as well as for the immune system activity in aged people. METHODS: Thirty elderly women aged 62 to 86 were subjected to a two-years authorized physical activity program. Peripheral blood lymphocytes distribution and the production of cytokines involved in the immune response development and regulation (IL-2, IL-4 and IFN-γ) were investigated. The same parameters were evaluated in two control groups of women: a sedentary group of 12 elderly women selected for the second round of the physical activity program and in a group of 20 sedentary young women. Flow cytometry methods were used for the examination of surface markers on peripheral blood lymphocytes and intracellular cytokines expression. RESULTS: The distribution of the main lymphocytes subpopulations in the peripheral blood of elderly women did not show changes after long-term moderate physical training. The percentage of lymphocytes expressing intracellular IL-2 was higher in the group of women attending 2-years physical activity program than in the control group of elderly sedentary women, and it was similar to the value estimated in the group of young sedentary women. There was no difference in the intracellular expression of IL-4 and IFN-γ between the active and elderly sedentary women. CONCLUSIONS: Our results suggest that moderate, long-term physical activity in elderly women may increase the production of IL-2, an important regulator of the immune response. This may help ameliorate immunosenescence in these women

Exactness of Belief Propagation for Some Graphical Models with Loops

It is well known that an arbitrary graphical model of statistical inference defined on a tree, i.e. on a graph without loops, is solved exactly and efficiently by an iterative Belief Propagation (BP) algorithm convergent to unique minimum of the so-called Bethe free energy functional. For a general graphical model on a loopy graph the functional may show multiple minima, the iterative BP algorithm may converge to one of the minima or may not converge at all, and the global minimum of the Bethe free energy functional is not guaranteed to correspond to the optimal Maximum-Likelihood (ML) solution in the zero-temperature limit. However, there are exceptions to this general rule, discussed in \cite{05KW} and \cite{08BSS} in two different contexts, where zero-temperature version of the BP algorithm finds ML solution for special models on graphs with loops. These two models share a key feature: their ML solutions can be found by an efficient Linear Programming (LP) algorithm with a Totally-Uni-Modular (TUM) matrix of constraints. Generalizing the two models we consider a class of graphical models reducible in the zero temperature limit to LP with TUM constraints. Assuming that a gedanken algorithm, g-BP, funding the global minimum of the Bethe free energy is available we show that in the limit of zero temperature g-BP outputs the ML solution. Our consideration is based on equivalence established between gapless Linear Programming (LP) relaxation of the graphical model in the $T\to 0$ limit and respective LP version of the Bethe-Free energy minimization.Comment: 12 pages, 1 figure, submitted to JSTA

Belief Propagation and Loop Series on Planar Graphs

We discuss a generic model of Bayesian inference with binary variables defined on edges of a planar graph. The Loop Calculus approach of [1, 2] is used to evaluate the resulting series expansion for the partition function. We show that, for planar graphs, truncating the series at single-connected loops reduces, via a map reminiscent of the Fisher transformation [3], to evaluating the partition function of the dimer matching model on an auxiliary planar graph. Thus, the truncated series can be easily re-summed, using the Pfaffian formula of Kasteleyn [4]. This allows to identify a big class of computationally tractable planar models reducible to a dimer model via the Belief Propagation (gauge) transformation. The Pfaffian representation can also be extended to the full Loop Series, in which case the expansion becomes a sum of Pfaffian contributions, each associated with dimer matchings on an extension to a subgraph of the original graph. Algorithmic consequences of the Pfaffian representation, as well as relations to quantum and non-planar models, are discussed.Comment: Accepted for publication in Journal of Statistical Mechanics: theory and experimen