1,010 research outputs found
The DNA methylation inhibitor 5-aza-2’-deoxycytidine retards cell growth and alters gene expression in canine mammary gland tumor cells
Disruption of gene expression by DNA methylation changes is widely involved in tumorigenesis. Here,to investigate DNA methylation changes in canine, we treated a canine mammary gland tumor cell line with a DNA methylation inhibitor, 5-aza-2’-deoxycytidine (5-aza). Cell growth was significantly retarded following 5-aza treatment and the epithelial marker genes CDH1 and KRT18 were significantly up-regulated, whereas the mesenchymal marker genes CDH2 and VIM were significantly downregulated. We also found a significant decrease in DNA methylation level in the CDH1 promoter region by 5-aza treatment. These results showed for the first time in canine mammary gland tumor cells that inhibition of DNA methylation caused cell growth retardation and affected epithelial mesenchymal transition-related gene expression via changes in DNA methylation level
Approximate Span Programs
Span programs are a model of computation that have been used to design
quantum algorithms, mainly in the query model. For any decision problem, there
exists a span program that leads to an algorithm with optimal quantum query
complexity, but finding such an algorithm is generally challenging.
We consider new ways of designing quantum algorithms using span programs. We
show how any span program that decides a problem can also be used to decide
"property testing" versions of , or more generally, approximate the span
program witness size, a property of the input related to . For example,
using our techniques, the span program for OR, which can be used to design an
optimal algorithm for the OR function, can also be used to design optimal
algorithms for: threshold functions, in which we want to decide if the Hamming
weight of a string is above a threshold or far below, given the promise that
one of these is true; and approximate counting, in which we want to estimate
the Hamming weight of the input. We achieve these results by relaxing the
requirement that 1-inputs hit some target exactly in the span program, which
could make design of span programs easier.
We also give an exposition of span program structure, which increases the
understanding of this important model. One implication is alternative
algorithms for estimating the witness size when the phase gap of a certain
unitary can be lower bounded. We show how to lower bound this phase gap in some
cases.
As applications, we give the first upper bounds in the adjacency query model
on the quantum time complexity of estimating the effective resistance between
and , , of , and, when is a lower
bound on , by our phase gap lower bound, we can obtain , both using space
Generating facets for the cut polytope of a graph by triangular elimination
The cut polytope of a graph arises in many fields. Although much is known
about facets of the cut polytope of the complete graph, very little is known
for general graphs. The study of Bell inequalities in quantum information
science requires knowledge of the facets of the cut polytope of the complete
bipartite graph or, more generally, the complete k-partite graph. Lifting is a
central tool to prove certain inequalities are facet inducing for the cut
polytope. In this paper we introduce a lifting operation, named triangular
elimination, applicable to the cut polytope of a wide range of graphs.
Triangular elimination is a specific combination of zero-lifting and
Fourier-Motzkin elimination using the triangle inequality. We prove sufficient
conditions for the triangular elimination of facet inducing inequalities to be
facet inducing. The proof is based on a variation of the lifting lemma adapted
to general graphs. The result can be used to derive facet inducing inequalities
of the cut polytope of various graphs from those of the complete graph. We also
investigate the symmetry of facet inducing inequalities of the cut polytope of
the complete bipartite graph derived by triangular elimination.Comment: 19 pages, 1 figure; filled details of the proof of Theorem 4, made
many other small change
Shared Randomness and Quantum Communication in the Multi-Party Model
We study shared randomness in the context of multi-party number-in-hand
communication protocols in the simultaneous message passing model. We show that
with three or more players, shared randomness exhibits new interesting
properties that have no direct analogues in the two-party case.
First, we demonstrate a hierarchy of modes of shared randomness, with the
usual shared randomness where all parties access the same random string as the
strongest form in the hierarchy. We show exponential separations between its
levels, and some of our bounds may be of independent interest. For example, we
show that the equality function can be solved by a protocol of constant length
using the weakest form of shared randomness, which we call "XOR-shared
randomness."
Second, we show that quantum communication cannot replace shared randomness
in the k-party case, where k >= 3 is any constant. We demonstrate a promise
function GP_k that can be computed by a classical protocol of constant length
when (the strongest form of) shared randomness is available, but any quantum
protocol without shared randomness must send n^Omega(1) qubits to compute it.
Moreover, the quantum complexity of GP_k remains n^Omega(1) even if the "second
strongest" mode of shared randomness is available. While a somewhat similar
separation was already known in the two-party case, in the multi-party case our
statement is qualitatively stronger:
* In the two-party case, only a relational communication problem with similar
properties is known.
* In the two-party case, the gap between the two complexities of a problem
can be at most exponential, as it is known that 2^(O(c)) log n qubits can
always replace shared randomness in any c-bit protocol. Our bounds imply that
with quantum communication alone, in general, it is not possible to simulate
efficiently even a three-bit three-party classical protocol that uses shared
randomness.Comment: 14 pages; v2: improved presentation, corrected statement of Theorem
2.1, corrected typo
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