162 research outputs found
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
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 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
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