The objective of the present study was to identify the leptin gene expression and the leptin receptor polymorphisms in blood samples and to correlate gene expression values with anthropometric characteristics.
Blood from 140 Greek young volunteers was subjected to polymerase chain reaction–restricted fragment length polymorphism (PCR–RFLP), for the genomic region of Q223R polymorphism at codon 223 in the leptin receptor gene (LEPR) coding region. RNA extraction, cDNA synthesis and Quantitative Real-Time PCR was performed for assessing the expression of the leptin gene (LEP).
Leptin gene was identified in all tested specimens and the gene was expressed in 88.9% of all volunteers with BMI < 25. In addition, it was observed that gene expression is affected by various external factors, such as Body Mass Index (BMI), eating behavior, gender and age. It was also shown that as for the Q223R polymorphism (A to G) allele G occurs with a frequency of 100% in men with BMI > 30 and 75.9% in men and 88.9% in women with BMI 25–30. Volunteers with BMI 25–30 who were homozygous on the G allele were 50% and 77.8% in men and women respectively. All subjects with a BMI > 30 were homozygous on the G allele at 100%.
In this small-scale study, results have shown that the leptin gene expression correlates with BMI and that the allele G in Q223R polymorphism is linked to overweight individuals.
Citation: Panagiotis Halvatsiotis, Argyris Siatelis, Panagiotis Koulouvaris, Anthimia Batrinou, Despina Vougiouklaki, Eleni Routsi, Michail Papapanou, Maria Trapali, Dimitra Houhoula. Comparison of Q223R leptin receptor polymorphism to the leptin gene expression in Greek young volunteers[J]. AIMS Medical Science, 2021, 8(4): 301-310. doi: 10.3934/medsci.2021025
[1] |
Linglong Du, Min Yang .
Pointwise long time behavior for the mixed damped nonlinear wave equation in |
[2] |
Linglong Du .
Long time behavior for the visco-elastic damped wave equation in |
[3] | Hantaek Bae . On the local and global existence of the Hall equations with fractional Laplacian and related equations. Networks and Heterogeneous Media, 2022, 17(4): 645-663. doi: 10.3934/nhm.2022021 |
[4] | Günter Leugering, Sergei A. Nazarov, Jari Taskinen . The band-gap structure of the spectrum in a periodic medium of masonry type. Networks and Heterogeneous Media, 2020, 15(4): 555-580. doi: 10.3934/nhm.2020014 |
[5] | Seung-Yeal Ha, Gyuyoung Hwang, Hansol Park . Emergent behaviors of Lohe Hermitian sphere particles under time-delayed interactions. Networks and Heterogeneous Media, 2021, 16(3): 459-492. doi: 10.3934/nhm.2021013 |
[6] | Arianna Giunti . Convergence rates for the homogenization of the Poisson problem in randomly perforated domains. Networks and Heterogeneous Media, 2021, 16(3): 341-375. doi: 10.3934/nhm.2021009 |
[7] | Francesca Alessio, Piero Montecchiari, Andrea Sfecci . Saddle solutions for a class of systems of periodic and reversible semilinear elliptic equations. Networks and Heterogeneous Media, 2019, 14(3): 567-587. doi: 10.3934/nhm.2019022 |
[8] | Ciro D'Apice, Olha P. Kupenko, Rosanna Manzo . On boundary optimal control problem for an arterial system: First-order optimality conditions. Networks and Heterogeneous Media, 2018, 13(4): 585-607. doi: 10.3934/nhm.2018027 |
[9] | María Anguiano, Francisco Javier Suárez-Grau . Newtonian fluid flow in a thin porous medium with non-homogeneous slip boundary conditions. Networks and Heterogeneous Media, 2019, 14(2): 289-316. doi: 10.3934/nhm.2019012 |
[10] | Wen Shen . Traveling waves for conservation laws with nonlocal flux for traffic flow on rough roads. Networks and Heterogeneous Media, 2019, 14(4): 709-732. doi: 10.3934/nhm.2019028 |
The objective of the present study was to identify the leptin gene expression and the leptin receptor polymorphisms in blood samples and to correlate gene expression values with anthropometric characteristics.
Blood from 140 Greek young volunteers was subjected to polymerase chain reaction–restricted fragment length polymorphism (PCR–RFLP), for the genomic region of Q223R polymorphism at codon 223 in the leptin receptor gene (LEPR) coding region. RNA extraction, cDNA synthesis and Quantitative Real-Time PCR was performed for assessing the expression of the leptin gene (LEP).
Leptin gene was identified in all tested specimens and the gene was expressed in 88.9% of all volunteers with BMI < 25. In addition, it was observed that gene expression is affected by various external factors, such as Body Mass Index (BMI), eating behavior, gender and age. It was also shown that as for the Q223R polymorphism (A to G) allele G occurs with a frequency of 100% in men with BMI > 30 and 75.9% in men and 88.9% in women with BMI 25–30. Volunteers with BMI 25–30 who were homozygous on the G allele were 50% and 77.8% in men and women respectively. All subjects with a BMI > 30 were homozygous on the G allele at 100%.
In this small-scale study, results have shown that the leptin gene expression correlates with BMI and that the allele G in Q223R polymorphism is linked to overweight individuals.
In this paper, we study the pointwise long time behavior of the solution for the nonlinear wave equation with frictional and visco-elastic damping terms
{∂2tu−c2Δu+ν1∂tu−ν2∂tΔu=f(u),u|t=0=u0(x),ut|t=0=u1(x), | (1) |
in multi-dimensional half space
(a1∂x1u+a2u)(x1=0,x′,t)=0. | (2) |
Over the past few decades, many mathematicians have concentrated on solving different kinds of damped nonlinear wave equations. The first kind is called the frictional damped wave equation, which is given as follows
{∂2tu−c2Δu+ν∂tu=f(u),u|t=0=u0(x),ut|t=0=u1(x), | (3) |
see [9,19,20,23] for the references. It is showed that for the long time, the fundamental solution for the linear system of (3) behaves like the Gauss kernel
{∂2tu−c2Δu−ν∂tΔu=f(u),u|t=0=u0(x),ut|t=0=u1(x). | (4) |
One can refer to [22] for the decaying rate of the linear solution, [11,12] for the asymptotic profiles of the linear problem, [4,21] for the nonlinear equation, etc. In [9], the authors studied the fundamental solution for the linear system of (4). The results show that the hyperbolic wave transport mechanism and the visco-elastic damped mechanism interact with each other so that the solution behaves like the convented heat kernel, i.e.,
For the initial-boundary value problem of the different damped wave equations, many authors studied the global well-posedness existence, long time behaviors, global attractors and decaying rate estimates of some elementary wave by using delicate energy estimate method, for example [1,13,25,26,28,29]. In this paper, we will use the pointwise estimate technique to give the long time behavior of the solution for system (1) with boundary condition (2). The main part of this technique is the construction and estimation of the Green's functions for the following linear systems:
{∂2tG1−c2ΔG1+ν1∂tG1−ν2∂tΔG1=0,x1,y1>0,x′∈Rn−1,t>0,G1(x1,x′,0;y1)=δ(x1−y1)δ(x′),G1t(x1,x′,0;y1)=0,a1∂x1G1(0,x′,t;y1)+a2G1(0,x′,t;y1)=0; | (5) |
{∂2tG2−c2ΔG2+ν1∂tG2−ν2∂tΔG2=0,x1,y1>0,x′∈Rn−1,t>0,G2(x1,x′,0;y1)=0,G2t(x1,x′,0;y1)=δ(x1−y1)δ(x′),a1∂x1G2(0,x′,t;y1)+a2G2(0,x′,t;y1)=0. | (6) |
The way of estimating the Green's functions
With the help of the accurate expression of Green's functions for the linear half space problem and the Duhamel's principle, we get the pointwise long time behavior for the nonlinear solution
Theorem 1.1. Let
|∂αxu0,∂αxu1|≤O(1)ε(1+|x|2)−r, r>n2, |α|≤1, |
|∂αxu(x,t)|≤O(1)ε(1+t)−|α|/2(1+t+|x|2)−n2. |
Moreover, we get the following optimal
‖∂αxu(⋅,t)‖Lp(Rn+)≤O(1)ε(1+t)−n2(1−1p)−|α|2, p∈(1,∞]. |
Remark 1. We can develop a similar theorem for the case of higher space dimension with a suitable choice of
Notations. Let
f(ξ,t):=F[f](ξ,t)=∫Rne−iξ⋅xf(x,t)dx,f(x,s):=L[f](x,s)=∫∞0e−stf(x,t)dt. |
The rest of paper is arranged as follows: in Section 2, we study the fundamental solutions for the linear Cauchy problem and give a pointwise description of the fundamental solutions in
The fundamental solutions for the linear damped wave equations are defined by
{∂2tG1−c2ΔG1+ν1∂tG1−ν2∂tΔG1=0G1(x,0)=δ(x),G1t(x,0)=0, | (7) |
{∂2tG2−c2ΔG2+ν1∂tG2−ν2∂tΔG2=0G2(x,0)=0,G2t(x,0)=δ(x). | (8) |
Applying the Fourier transform to (7) and (8) in the space variable
G1(ξ,t)=σ+eσ−t−σ−eσ+tσ+−σ−, G2(ξ,t)=eσ+t−eσ−tσ+−σ−,σ±=−ν1+ν2|ξ|22±12√ν21+(2ν1ν2−4c2)|ξ|2+ν22|ξ|4. |
In [16], authors have studied the pointwise estimates of the fundamental solutions by long wave-short wave decomposition in the Fourier space. Here we will use the local analysis and inverse Fourier transform to get the pointwise structures of the fundamental solutions in the physical variables
f(x,t)=fL(x,t)+fS(x,t),F[fL]=H(1−|ξ|ε0)F[f](ξ,t),F[fS]=(1−H(1−|ξ|ε0))F[f](ξ,t), |
with the parameter
H(x)={1, x>0,0, x<0. |
Long wave component. When
{σ+=−c2|ξ|2ν1+o(|ξ|2),σ−=−ν1+(−ν2+c2ν1)|ξ|2+o(|ξ|2), |
σ+−σ−=ν1+(ν1ν2−2c2)|ξ|2ν1+o(|ξ|2). |
Then
σ+eσ−t=(−c2|ξ|2ν1+o(|ξ|2))e(−ν1+(−ν2+c2ν1)|ξ|2+o(|ξ|2))t=−c2ν1|ξ|2e−ν1t+o(|ξ|2)e−Ct,σ−eσ+t=(−ν1+(−ν2+c2ν1)|ξ|2+o(|ξ|2))e(−c2|ξ|2ν1+o(|ξ|2))t=−ν1e−c2ν1|ξ|2t+O(|ξ|2)e−C|ξ|2t,1σ+−σ−=1ν1+O(|ξ|2). |
So we can approximate the fundamental solutions as follows
σ+eσ−t−σ−eσ+tσ+−σ−=−c2|ξ|2ν21e−ν1t+e−c2ν1|ξ|2t+o(|ξ|2)e−Ct+O(|ξ|2)e−C|ξ|2t,eσ+t−eσ−tσ+−σ−=1ν1e−c2ν1|ξ|2t−1ν1e−ν1t+O(|ξ|2)e−Ct+o(|ξ|2)e−C|ξ|2t. |
Using Lemma 5.1 in Appendix, for
|DαxGL1(x,t)|≤O(1)(e−|x|2C(t+1)(1+t)n+|α|2+e−|x|+tC),|DαxGL2(x,t)|≤O(1)(e−|x|2C(t+1)(1+t)n+|α|2+e−|x|+tC). |
Short wave component. We adopt the local analysis method to give a description about all types of singular functions for the short wave component of the fundamental solutions. When
{σ+=−c2ν2+c2(ν1ν2−c2)ν321|ξ|2+O(|ξ|−4),σ−=−σ+−(ν1+ν2|ξ|2). |
This non-decaying property results in the singularities of the fundamental solution
{σ∗+=−c2ν2+c2(ν1ν2−c2)ν32(11+|ξ|2+1(1+|ξ|2)2)+c2(ν1ν2−c2)ν32O((1+|ξ|2)−3),σ∗−=−σ∗+−(ν1+ν2|ξ|2), |
infξ∈Dε0|σ∗−(ξ)−σ∗+(ξ)|>0,supξ∈Dε0Re(σ∗±(ξ))≤−J0, supξ∈Dε0|ξ|8|σ±(ξ)−σ∗±(ξ)|<∞ as |ξ|→∞. |
Therefore, the approximated analytic spectra
|σ+eσ−t−σ−eσ+tσ+−σ−−σ∗+eσ∗−t−σ∗−eσ∗+tσ∗+−σ∗−, eσ+t−eσ−tσ+−σ−−eσ∗+t−eσ∗−tσ∗+−σ∗−|≤O(1)(1+|ξ|2)4. |
By Lemma 5.4 in the Appendix, we have
‖F−1[σ+eσ−t−σ−eσ+tσ+−σ−−σ∗+eσ∗−t−σ∗−eσ∗+tσ∗+−σ∗−](⋅,t)‖L∞(Rn)=O(1),‖F−1[eσ+t−eσ−tσ+−σ−−eσ∗+t−eσ∗−tσ∗+−σ∗−](⋅,t)‖L∞(Rn)=O(1), |
which asserts that all singularities are contained in
Now we seek out all the singularities. For the short wave part of
σ∗+eσ∗−t−σ∗−eσ∗+tσ∗+−σ∗−=eσ∗+t−σ∗+eσ∗+tσ∗+−σ∗−+σ∗+eσ∗−tσ∗+−σ∗−. |
The first term is
eσ∗+t=e−c2tν2ec2(ν1ν2−c2)tν3211+|ξ|2+c2(ν1ν2−c2)tν321(1+|ξ|2)2+c2(ν1ν2−c2)tν32O(1(1+|ξ|2)3)=e−c2tν2(1+c2(ν1ν2−c2)tν3211+|ξ|2+c2(ν1ν2−c2)tν321(1+|ξ|2)2)+e−c2tν2c2(ν1ν2−c2)tν32O(1(1+|ξ|2)3)=e−c2tν2+c2(ν1ν2−c2)ν32te−c2tν21+|ξ|2+c2(ν1ν2−c2)ν32te−c2tν2(1+|ξ|2)2+te−c2tν2c2(ν1ν2−c2)ν32O(1(1+|ξ|2)3). |
It can be estimated as follows
|F−1[eσ∗+t]−e−c2t/ν2δ(x)−tc2(ν1ν2−c2)ν−32e−c2t/ν2Yn(x)|≤Ce−|x|+tC. |
The second term contains no singularities and we have
σ∗+eσ∗+tσ∗+−σ∗−=−c2ν−22e−c2t/ν21+|ξ|2+e−c2tν2O(1(1+|ξ|2)2), |
so
|F−1[σ∗+eσ∗+tσ∗+−σ∗−]+c2v−22e−c2t/v2Yn(x)|≤Ce−|x|+tC. |
For the third term, the function
|σ∗+eσ∗−tσ∗+−σ∗−|≤K0e−|ξ|2t/C1−J∗0t1+|ξ|2, |
∫Im(ξk)=δ1≤k≤n|σ∗+eσ∗−tσ∗+−σ∗−|dξ≤C∫Rne−|ξ|2t/C−J∗0t(1+|ξ|)2dξ=CΓ(n)∫∞0e−r2t/C−J∗0t(1+r)2rn−1dr≤Ce−t/CLn(t), | (9) |
where
Ln(t)≡{1,n=1,log(t),n=2,t−n−22,n≥3. |
We denote
j1(x,t):=F−1[σ∗+eσ∗−tσ∗+−σ∗−], |
following the way of proof for Lemma 5.4, we get
|j1(x,t)|≤Ce−(|x|+t)/CLn(t) |
from (9). So the following estimate for
|GS1(x,t)−j1(x,t)−e−c2t/ν2δn(x)−(tc2ν−32(ν1ν2−c2)+c2ν−22)e−c2t/ν2Yn(x)|≤e−|x|+tC. |
For the short wave part of
eσ∗+t−eσ∗−tσ∗+−σ∗−=eσ∗+tσ∗+−σ∗−−eσ∗−tσ∗+−σ∗−. |
The first term is
eσ∗+tσ∗+−σ∗−=ν−12e−c2t/ν21+|ξ|2+e−c2tν2O(1(1+|ξ|2)2), |
and we have
|F−1[eσ∗+tσ∗+−σ∗−]−ν−12e−c2t/ν2Yn(x)|≤Ce−|x|+tC. |
The second term contains no singularities. If denoting
j2(x,t)≡−F−1(eσ∗−tσ∗+−σ∗−), |
then there exists
|j2(x,t)|≤Ce−(|x|+t)/CLn(t), |
and we have the following estimate for
|GS2(x,t)−j2(x,t)−ν−12e−c2t/ν2Yn(x)|≤Ce−|x|+tC. |
Hence the short wave components have the following estimates in the finite Mach number region
|GS1(x,t)−j1(x,t)−e−c2tν2δn(x)−(tc2(ν1ν2−c2)ν32+c2ν22)e−c2tν2Yn(x)|≤Ce−|x|+tC.|GS2(x,t)−j2(x,t)−ν−12e−c2tν2Yn(x)|≤Ce−|x|+tC. |
Outside the finite Mach number region
We choose the weighted function
wt=−aMw,∇w=xM|x|w,Δw=wM2. |
Consider the linear damped wave equation outside the finite Mach number region:
{∂2tui−c2Δui+ν1∂tui−ν2∂tΔui=0,|x|≥3(t+1),ui|t=0=0,uit|t=0=0,ui||x|=3(t+1)=Gi||x|=3(t+1). | (10) |
Denote the outside finite Mach number region
c2∫∂Dtw∂tui∇ui⋅d→Sx+ν2∫∂Dtw∂tui∂t∇ui⋅d→Sx=12ddt∫Dtw((∂tui)2+c2|∇ui|2)dx+∫Dt(ν1w−12wt−12ν2Δw)(∂tui)2dx+c2∫Dt∂tui∇w⋅∇uidx+ac22M∫Dtw|∇ui|2dx+ν2∫Dtw|∂t∇ui|2dx=12ddt∫Dtw((∂tui)2+c2|∇ui|2)dx+∫Dt(ν1+a2M−ν22M2)w(∂tui)2dx+c2∫Dtw∂tuixM|x|⋅∇uidx+ac22M∫Dtw|∇ui|2dx+ν2∫Dtw|∂t∇ui|2dx≥12ddt∫Dtw((∂tui)2+c2|∇ui|2)dx+∫Dtw(ac24M|∇ui|2+(ν12+a2M−ν22M2)(∂tui)2+ν2|∂t∇ui|2)dx. |
On the boundary
|∂tui|,|∇ui|,|∂t∇ui|≤Ce−Ct, x∈∂Dt. |
So
ddt∫Dtw((∂tui)2+c2|∇ui|2)dx+2δ0∫Dtw((∂tui)2+c2|∇ui|2)dx≤Ce−Ct, | (11) |
One can also get similar estimates for any higher order derivatives
l∑|α|=1(ddt∫Rnw((∂t∂αxui)2+c2|∇∂αxui|2)dx) +δ|α|∫Rnw((∂t∂αxui)2+c2|∇∂αxui|2)dx)≤Ce−Ct. | (12) |
Integrating (11) and (12) over
sup(x,t)∈Dt((∂t∂αxui)2+c2|∇∂αxui|2)≤Ce−(|x|−at)/C≤Ce−(|x|+t)/C, for |α|<l−n2, |
since
|DαxGi(x,t)|≤Ce−(|x|+t)/C, for |α|<l−n2. |
To summarize, we have the following pointwise estimates for the fundamental solutions:
Lemma 2.1. The fundamental solutions have the following estimates for all
|Dαx(G1(x,t)−j1(x,t)−e−c2t/ν2δn(x)−(tc2ν−32(ν1ν2−c2)+c2ν−22)e−c2t/ν2Yn(x))|≤O(1)(e−|x|2C(t+1)(t+1)n+|α|2+e−(|x|+t)/C),|Dαx(G2(x,t)−j2(x,t)−ν−12e−c2t/ν2Yn(x))|≤O(1)(e−|x|2C(t+1)(t+1)n+|α|2+e−(|x|+t)/C). |
Here
|j1(x,t),j2(x,t)|≤O(1)Ln(t)e−(|x|+t)/C,L2(t)=log(t), Ln(t)=t−n−22 for n≥3,Y2(x)=O(1)12πBesselK0(|x|), Yn(x)=O(1)e−|x||x|n−2 for n≥3. |
Applying Laplace transform in
G1(ξ,s)=s+ν1+ν2|ξ|2s2+ν1s+(c2+ν2s)|ξ|2, G2(ξ,s)=1s2+ν1s+(c2+ν2s)|ξ|2. |
Now we give a lemma:
Lemma 2.2.
12π∫Reiξ1x1s2+ν1s+ν2s|ξ|2+c2|ξ|2dξ1=1ν2s+c2e−λ|x1|2λ, |
where
Proof. We prove it by using the contour integral and the residue theorem. Note that
12π∫Reiξ1x1s2+ν1s+ν2s|ξ|2+c2|ξ|2dξ1=12π1ν2s+c2∫Reiξ1x1ξ21+|ξ′|2+s2+ν1sν2s+c2dξ1=12π1ν2s+c2∫Reiξ1x1(ξ1−λi)(ξ1+λi)dξ1. |
Define a closed path
If
12π1ν2s+c2∫Reiξ1x1(ξ1−λi)(ξ1+λi)dξ1=12π1ν2s+c22πiRes(eiξ1x1(ξ1−λi)(ξ1+λi)|ξ1=λi)=e−λx12(ν2s+c2)λ. |
The computation for the case
12π1ν2s+c2∫Reiξ1x1(ξ1−λi)(ξ1+λi)dξ1=−12π1ν2s+c22πiRes(eiξ1x1(ξ1−λi)(ξ1+λi)|ξ1=−λi)=eλx12(ν2s+c2)λ. |
Hence we prove this lemma.
With the help of Lemma 2.2, we get the expression of fundamental solutions
G1(x1,ξ′,s)=1ν2s+c2(ν2δ(x1)+c2(s+ν1)ν2s+c2e−λ|x1|2λ),G2(x1,ξ′,s)=e−λ|x1|2λ(ν2s+c2). |
In particular, when
G1(−ˉx1,ξ′,s)=c2(s+ν1)(ν2s+c2)2e−λˉx12λ, G2(−ˉx1,ξ′,s)=e−λˉx12λ(ν2s+c2). |
In this section, we will give the pointwise estimates of the Green's functions for the initial boundary value problem. Firstly, we compute the transformed Green's functions in the partial-Fourier and Laplace transformed space. Then by comparing the symbols of the fundamental solutions and the Green's functions in this transformed space, we get the simplified expressions of Green's functions for the initial-boundary value problem. With the help of the pointwise estimates of the fundamental solutions and boundary operator, we finally get the sharp estimates of Green functions for the half space linear problem.
Before computing, we make the initial value zero by considering the error function
{∂2tRi−c2ΔRi+ν1∂tRi−ν2∂tΔRi=0,x∈Rn+,t>0,Ri|t=0=0,Rit|t=0=0,(a1∂x1+a2)Ri(0,x′,t;y1)=−(a1∂x1+a2)Gi(x1−y1,x′,t)|x1=0. |
Taking Fourier transform only with respect to the tangential spatial variable
{(s2+ν1s)Ri−(c2+ν2s)Rix1x1+(c2+ν2s)|ξ′|2Ri=0,(a1∂x1+a2)Ri(0,ξ′,s;y1)=(a1∂y1−a2)Gi(−y1,ξ′,s)=−(a1λ+a2)Gi(−y1,ξ′,s). |
Solving it and dropping out the divergent mode as
Ri(x1,ξ′,s;y1)=−a1λ+a2a2−a1λe−λx1Gi(−y1,ξ′,s)=−a1λ+a2a2−a1λGi(x1+y1,ξ′,s), |
where
Therefore the transformed Green's functions
Gi(x1,ξ′,s;y1)=Gi(x1−y1,ξ′,s)−a1λ+a2a2−a1λGi(x1+y1,ξ′,s)=Gi(x1−y1,ξ′,s)+Gi(x1+y1,ξ′,s)−2a2a2−a1λGi(x1+y1,ξ′,s), |
which reveal the connection between fundamental solutions and the Green's functions.
Hence,
Gi(x1,x′,t;y1)=Gi(x1−y1,x′,t)+Gi(x1+y1,x′,t)−F−1ξ′→x′L−1s→t[2a2a2−a1λ]∗x′,tGi(x1+y1,x′,t). |
Now we estimate the boundary operator
Instead of inverting the boundary symbol, we follow the differential equation method. Notice that
F−1ξ′→x′L−1s→t[2a2a2−a1λGi(x1+y1,ξ′,s)]=2a2a1∂x1+a2Gi(x1+y1,x′,t), |
setting
g(x1,x′,t)≡2a2a1∂x1+a2Gi(x1,x′,t), |
then the function
(a2+a1∂x1)g=2a2Gi(x1,x′,t). |
Solving this ODE gives
g(x1,x′,t)=2γ∫∞x1e−γ(z−x1)Gi(z,x′,t)dz=2γ∫∞0e−γzGi(x1+z,x′,t)dz. | (13) |
Summarizing previous results we obtain
Lemma 3.1. The Green's functions
Gi(x1,x′,t;y1)=GLi(x1,x′,t;y1)+GSi(x1,x′,t;y1). |
Meanwhile, the following estimates hold:
|DαxGLi(x1,x′,t;y1)|≤O(1)(e−(x1−y1)2+(x′−y′)2C(t+1)(t+1)n+|α|2+e−(x1+y1)2+(x′−y′)2C(t+1)(t+1)n+|α|2),|α|≥0; |
|GS1(x1,x′,t;y1)|≤O(1)(j1(x1−y1,x′,t)+j1(x1+y1,x′,t)+e−c2tν2(δn(x1−y1,x′)+δn(x1+y1,x′))+e−c2tν2(tc2ν−32(ν1ν2−c2)+c2ν−22)(Yn(x1−y1,x′)+Yn(x1+y1,x′))) |
and
|GS2(x1,x′,t;y1)|≤O(1)(j1(x1−y1,x′,t)+j2(x1+y1,x′,t)+ν−12e−c2tν2(Yn(x1−y1,x′)+Yn(x1+y1,x′))). |
Proof. Note that
Gi(x1,x′,t;y1)=Gi(x1−y1,x′,t)+Gi(x1+y1,x′,t)−g(x1+y1,x′,t), |
based on the long-wave short-wave decomposition of the fundamental solutions
Gi(x,t)=GLi(x,t)+GSi(x,t), |
we can write
GLi(x1,x′,t;y1)=O(1)(GLi(x1−y1,x′,t)+GLi(x1+y1,x′,t)),GSi(x1,x′,t;y1)=O(1)(GSi(x1−y1,x′,t)+GSi(x1+y1,x′,t)), |
and get the estimates directly from Lemma 2.1 and (13).
The study of boundary operator in the last section suggests that we can only consider the case
Now we give the pointwise long time behavior of the solution for the nonlinear problem and prove the Theorem 1.1. The Green's functions
∂αxu(x,t)=∂αx∫Rn+(G1(x1,x′−y′,t;y1)u0(y)+G2(x1,x′−y′,t;y1)u1(y))dy+∂αx∫t0∫Rn+G2(x1,x′−y′,t−τ;y1)f(u)(y,τ)dydτ≡∂αxI(x,t)+∂αxN(x,t). | (14) |
The initial part
∂αxI(x,t)=∂αxIL(x,t)+∂αxIS(x,t), |
where
∂αxIL(x,t)=∂αx∫Rn+(GL1(x1,x′−y′,t;y1)u0(y)+GL2(x1,x′−y′,t;y1)u1(y))dy∂αxIS(x,t)=∂αx∫Rn+(GS1(x1,x′−y′,t;y1)u0(y)+GS2(x1,x′−y′,t;y1)u1(y))dy. |
By lemma 5.2, we have the following estimates in the finite Mach number region
|IL(x,t)|≤O(1)ε∫Rn+e−(x−y)2C(t+1)(t+1)n2(1+|y|2)−rdy≤O(1)ε(e−x2C(t+1)(t+1)n2+(1+t+|x|2)−n2), | (15) |
|IS(x,t)|≤O(1)εe−(|x|+t)C|∫Rn(Ln(t)+δn(x−y) +[tc2ν32(ν1ν2−c2)+c2ν22]Yn(x−y))(1+|y|2)−rdy|+O(1)εe−(|x|+t)C|∫Rn(Ln(t)+ν−12Yn(x−y))(1+|y|2)−rdy|≤O(1)ε(e−x2C(t+1)(t+1)n2+(1+t+|x|2)−n2). | (16) |
Hence we combine (15) and (16) to get the estimate of the first part in (14) when
|I(x,t)|≤O(1)ε(e−x2C(t+1)(t+1)n2+(1+t+|x|2)−n2). | (17) |
Similarly, when
|∂αxI(x,t)|=|∂αxIL(x,t)+∂αxIS(x,t)|≤O(1)ε∫Rn+(e−(x1−y1)2+(x′−y′)2C(t+1)(t+1)n2+12+e−(x1+y1)2+(x′−y′)2C(t+1)(t+1)n2+12)(1+|y|2)−rdy+1{∂αx=∂x1}O(1)εe−(|x|+t)C|∫Rn−1Ln(t)+δn(x1−y1,x′−y′,t) +δn(x1+y1,x′−y′,t)+(tc2ν−32(ν1ν2−c2)+c2ν−22) (Yn(x1−y1,x′−y′)+Yn(x1+y1,x′−y′))(1+|y|2)−rdy′|y1=0|+O(1)εe−(|x|+t)C|∫Rn+Ln(t)+δn(x1−y1,x′−y′,t)+δn(x1+y1,x′−y′,t) +(tc2ν−32(ν1ν2−c2)+c2ν−22) (Yn(x1−y1,x′−y′)+Yn(x1+y1,x′−y′))(1+|y|2)−rdy|+1{∂αx=∂x1}O(1)εe−(|x|+t)C|∫Rn−1(Ln(t)+ν−11Yn(x1−y1,x′−y′) +ν−11Yn(x1+y1,x′−y′))(1+|y|2)−rdy′|y1=0|+O(1)εe−(|x|+t)C|∫Rn−1(Ln(t)+ν−11Yn(x1−y1,x′−y′) +ν−11Yn(x1+y1,x′−y′))(1+|y|2)−rdy|≤O(1)ε(1+t)−|α|2(e−x22C(t+1)(t+1)n2+(1+t+|x|2)−r)+O(1)εe−(|x|+t)/C. |
where
1{∂αx=∂x1}={1, if ∂αx=∂x1,0, otherwise. |
Here we use the integration by parts to estimate the short wave component part. Outside the finite Mach number region, we have
|∂αxI(x,t)|≤O(1)εe−ν1t∫Rn+e−|x−y|(1+y2)−rdy≤O(1)εe−ν1t(1+|x|2)−r,|α|≤1. | (18) |
Based on the estimates of (17)-(18), the ansatz is posed for the solution as follows:
|∂αxu(x,t)|≤O(1)ε(1+t)−|α|2(1+t+|x|2)−n2,|α|≤1. |
Straightforward computations show that
|f(u)(x,t)|≤O(1)εk(1+t+|x|2)−nk2. |
Now we justify the ansatz for the nonlinear term. For
|N(x,t)|=|∫t0∫Rn+G2(x1,x′−y′,t−τ;y1)f(u)(y,τ)dydτ|≤|∫t0∫Rn+GL2(x1,x′−y′,t−τ;y1)f(u)(y,τ)dydτ|+|∫t0∫Rn+GS2(x1,x′−y′,t−τ;y1)f(u)(y,τ)dydτ|=N1+N2. |
Using Lemma 5.3, one gets
N1≤O(1)εk|∫t0∫∞0∫Rn−1(e−(x1−y1)2+(x′−y′)2C(t−τ+1)(t−τ+1)n2+e−(x1+y1)2+(x′−y′)2C(t−τ+1)(t−τ+1)n2) (1+τ+|y|2)−nk2dy′dy1dτ|≤O(1)εk|∫t0∫Rne−(x1−y1)2+(x′−y′)2C(t−τ+1)(t−τ+1)n2(1+τ+|y|2)−nk2dydτ|≤O(1)εk(1+t+|x|2)−n2, |
N2≤O(1)εk|∫t0∫Rn+e−c2(t−τ)ν2(Ln(t−τ)+ν−12Yn(x1,x′−y′;y1)) (1+τ+|y|2)−nk2dydτ|≤O(1)εk(1+t+|x|2)−n2. |
Now we compute the estimate of
|∂αxN(x,t)|=|∂αx∫t0∫Rn+G2(x1,x′−y′,t−τ;y1)f(u)(y,τ)dydτ|≤|∫t0∫Rn+∂αxGL2(x1,x′−y′,t−τ;y1)f(u)(y,τ)dydτ|+|∫t0∫Rn+∂αxGS2(x1,x′−y′,t−τ;y1)f(u)(y,τ)dydτ|=∂αxN1+∂αxN2. |
Similarly we have
∂αxN1=|O(1)εk∫t0∫∞0∫Rn−1(e−(x1−y1)2+(x′−y′)2C(t−τ+1)(t−τ+1)n2+|α|2+e−(x1+y1)2+(x′−y′)2C(t−τ+1)(t−τ+1)n2+|α|2) (1+τ+|y|2)−nk2dy′dy1dτ|≤|O(1)εk∫t0∫Rne−(x1−y1)2+(x′−y′)2C(t−τ+1)(t−τ+1)n2+|α|2(1+τ+|y|2)−nk2dydτ|≤O(1)εk(1+t)−|α|2(1+t+|x|2)−n2, |
∂αxN2=|∫t0∫Rn+∂αxGS2(x1,x′−y′,t−τ;y1)f(u)(y,τ)dydτ|=1{∂αx=∂x1}|∫t0∫Rn−1GS2(x1,x′−y′,t−τ;y1)f(u)(y,τ)dy′|y1=0dτ|+|∫t0∫Rn+GS2(x1,x′−y′,t−τ;y1)∂αyf(u)(y,τ)dydτ|. | (19) |
The boundary term in (19) has the following estimates:
|∫t0∫Rn−1GS2(x1,x′−y′,t−τ;y1)f(u)(y,τ)dy′|y1=0dτ|≤|(∫t/20+∫tt/2)∫Rn−1GS2(x1,x′−y′,t−τ;y1)f(u)(y,τ)dy′|y1=0dτ|≤O(1)εk(1+t)−|α|2(1+t+|x|2)−n2. |
The second term in (19) satisfies
|∫t0∫Rn+GS2(x1,x′−y′,t−τ;y1)∂αyf(u)(y,τ)dydτ|≤|O(1)εk∫t0∫Rn+e−c2(t−τ)ν2(Ln(t−τ)+ν−12Yn(x1,x′−y′;y1))≤(1+τ)−|α|2(1+τ+|y|2)−nk2dydτ|≤O(1)εk(1+t)−|α|2(1+t+|x|2)−n2. |
Therefore one has the following estimate for the nonlinear term
|∂αxN|≤O(1)εk(1+t)−|α|2(1+t+|x|2)−n2,|α|≤1. |
Outside the finite Mach number region,
|∂αxN|≤O(1)εk|∫t0∫Rn+e−ν1(t−τ)e−|x−y|(1+τ+|y2|)−nk2dydτ|≤O(1)εk(1+t+|x|2)−nk2,|α|≤1. |
Thus, we verify the ansatz and finish the proof of pointwise estimates of the solution.
The
(∫Rn+(1+t+|x|2)−n2pdx)1p=(∫Rn+(1+t)−n2p(1+|x|21+t)−n2pdx)1p=(1+t)−n2(1+t)n2p=(1+t)−n2(1−1p). |
Hence we finish the proof of Theorem 1.1.
Lemma 5.1. [10] In the finite Mach number region
|1(2π)n∫|ξ|≤ε0(iξ)αeiξ⋅xe−1κ|ξ|2tdξ|≤O(1)e−|x|2C(t+1)(1+t)n+|α|2+O(1)e−|x|+tC,|α|≥0. |
Lemma 5.2. [9] We have the follow estimate for
∫Rne−(x−y)2C(t+1)(1+t)n2+|α|2(1+|y|2)−rdy≤O(1)(1+t)−|α|2(e−x22C(t+1)(t+1)n2+(1+t+|x|2)−r). |
Lemma 5.3. [9] For
∫t0∫Rne−ν(t−τ)2Yn(x−y)(1+τ)−|α|2(1+τ+|y|2)nk2dydτ≤O(1)(1+t)−|α|2(1+t+|x|)−nk/2, |
∫t0∫Rne−(x−y)2C(t−τ+1)(1+t)n2+|α|2(1+τ+|y|2)−nk2dydτ≤O(1)(1+t)−|α|2(1+t+|x|2)−n2. |
Lemma 5.4. [7] Suppose a function
|F[f](ξ)|≤E(1+|ξ|)n+1, for |Im(ξi)|≤δ, and i=1,2,⋯,n. |
Then, the function
|f(x)|≤Ee−δ|x|/C, |
for any positive constant
The authors would like to thank the referees very much for their valuable comments and suggestions which improve the presentation of papersignicantly.
[1] |
Francisco V, Pino J, Campos-Cabaleiro V, et al. (2018) Obesity, fat mass and immune system: role for leptin. Front Physiol 9: 640. doi: 10.3389/fphys.2018.00640
![]() |
[2] |
Poeggeler B, Schulz C, Pappolla MA, et al. (2010) Leptin and the skin: a new frontier. Exp Dermatol 19: 12-18. doi: 10.1111/j.1600-0625.2009.00930.x
![]() |
[3] |
Thompson DB, Ravussin E, Bennett PH, et al. (1997) Structure and sequence variation at the human leptin receptor gene in lean and obese Pima Indians. Hum Mol Genet 6: 675-679. doi: 10.1093/hmg/6.5.675
![]() |
[4] |
Jaganathan R, Ravindran R, Dhanasekaran S (2018) Emerging role of adipocytokines in type 2 diabetes as mediators of insulin resistance and cardiovascular disease. Can J Diabetes 42: 446-456.e1. doi: 10.1016/j.jcjd.2017.10.040
![]() |
[5] |
Feng R, Li Y, Zhao D, et al. (2009) Lack of association between TNF 238 G/A polymorphism and type 2 diabetes: a meta-analysis. Acta Diabetol 46: 339-343. doi: 10.1007/s00592-009-0118-3
![]() |
[6] |
Luna G, Rodrigues da Silva I, Sanchez M (2016) Association between -308G/A TNFα polymorphism and susceptibility to type 2 diabetes mellitus: a systematic review. J Diabetes Res 2016. doi: 10.1155/2016/6309484
![]() |
[7] |
Jamil K, Jayaraman A, Ahmad J, et al. (2017) TNF-alpha 308G/A and 238G/A polymorphisms and its protein network associated with type 2 diabetes mellitus. Saudi J Biol Sci 24: 1195-1203. doi: 10.1016/j.sjbs.2016.05.012
![]() |
[8] |
Thiem K, Stienstra R, Riksen NP, et al. (2019) Trained immunity and diabetic vascular disease. Clin Sci 133: 195-203. doi: 10.1042/CS20180905
![]() |
[9] |
Wild S, Roglic G, Green A, et al. (2004) Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care 27: 1047-1053. doi: 10.2337/diacare.27.5.1047
![]() |
[10] |
Duarte SFP, Francischetti EA, Genelhu-Abreu V, et al. (2006) p.Q223R leptin receptor polymorphism associated with obesity in Brazilian multiethnic subjects. Am J Hum Biol 18: 448-453. doi: 10.1002/ajhb.20519
![]() |
[11] |
Suriyaprom K, Tungtrongchitr R, Thawnasom K (2014) Measurement of the levels of leptin, BDNF associated with polymorphisms LEP G2548A, LEPR Gln223Arg and BDNF Val66Met in Thai with metabolic syndrome. Diabetol Metab Syndr 6: 1-9. doi: 10.1186/1758-5996-6-6
![]() |
[12] |
Murugesan D, Arunachalam T, Ramamurthy V, et al. (2010) Association of polymorphisms in leptin receptor gene with obesity and type 2 diabetes in the local population of Coimbatore. Indian J Hum Genet 16: 72-77. doi: 10.4103/0971-6866.69350
![]() |
[13] |
Illangasekera YA, Kumarasiri PVR, Fernando DJ, et al. (2020) Association of the leptin receptor Q223R (rs1137101) polymorphism with obesity measures in Sri Lankans. BMC Res Notes 13: 34. doi: 10.1186/s13104-020-4898-4
![]() |
[14] |
Yiannakouris N, Yannakoulia M, Melistas L, et al. (2001) The Q223R polymorphism of the leptin receptor gene is significantly associated with obesity and predicts a small percentage of body weight and body composition variability. J Clin Endocrinol Metab 86: 4434-4439. doi: 10.1210/jcem.86.9.7842
![]() |
[15] |
Marcos-Pasero H, Aguilar-Aguilar E, Colmenarejo G, et al. (2020) The Q223R polymorphism of the leptin receptor gene as a predictor of weight gain in childhood obesity and the identification of possible factors involved. Genes 11: 560. doi: 10.3390/genes11050560
![]() |
[16] |
Chiu KC, Chu A, Chuang LM, et al. (2004) Association of leptin receptor polymorphism with insulin resistance. Eur J Endocrinol 150: 725-729. doi: 10.1530/eje.0.1500725
![]() |
[17] |
Heo M, Leibel RL, Fontaine KR, et al. (2002) A meta-analytic investigation of linkage and association of common leptin receptor (LEPR) polymorphisms with body mass index and waist circumference. Int J Obes Relat Metab Disord 26: 640-646. doi: 10.1038/sj.ijo.0801990
![]() |
[18] |
Constantin A, Costache G, Sima AV, et al. (2010) Leptin G-2548A and leptin receptor Q223R gene polymorphisms are not associated with obesity in Romanian subjects. Biochem Biophys Res Commun 391: 282-286. doi: 10.1016/j.bbrc.2009.11.050
![]() |
[19] |
Becer E, Mehmetcik G, Bareke H, et al. (2013) Association of leptin receptor gene Q223R polymorphism on lipid profiles in comparison study between obese and non-obese subjects. Gene 529: 16-20. doi: 10.1016/j.gene.2013.08.003
![]() |
[20] |
Quinton N, Lee A, Ross R, et al. (2001) A single nucleotide polymorphism (SNP) in the leptin receptor is associated with BMI, fat mass and leptin levels in postmenopausal Caucasian women. Hum Genet 108: 233-236. doi: 10.1007/s004390100468
![]() |
[21] |
Chagnon YC, Chung WK, Pérusse L, et al. (1999) Linkages and associations between the leptin receptor (LEPR) gene and human body composition in the Quebec family study. Int J Obes Relat Metab Disord 23: 278-286. doi: 10.1038/sj.ijo.0800809
![]() |
[22] |
Guizar-Mendoza JM, Amador-Licona N, Flores-Martinez SE, et al. (2005) Association analysis of the Gln223Arg polymorphism in the human leptin receptor gene, and traits related to obesity in Mexican adolescents. J Hum Hypertens 19: 341-346. doi: 10.1038/sj.jhh.1001824
![]() |