Agent-Based Network Modeling Study of Immune Responses in Progression of Ulcerative Colitis

Ulcerative colitis, an inflammatory bowel disease, is a chronic inflammatory disorder that results in ulcers of the colon and rectum without known etiology.Ulcerative colitis causes a huge public health care burden particularly in developed countries.Many studies suggest that ulcerative colitis results from an abnormal immune response against components of commensal microbiota in genetically susceptible individuals.However, understanding of the disease mechanisms at cellular and molecular levels remains largely elusive.In this paper, a network model is developed based on our previous study and computer simulations are performed using an agent-based network modeling to elucidate the dynamics of immune response in ulcerative colitis progression.Our modeling study identifies several important positive feedback loops as a driving force for ulcerative colitis initiation and progression.The results demonstrate that although immune response in ulcerative colitis patients is dominated by anti-inflammatory/regulatory cells such as alternatively activated macrophages and type Ⅱ natural killer T cells, proinflammatory cells including classically activated macrophages, T helper 1 and T helper 17 cells, and their secreted cytokines tumor necrosis factor-α, interleukin-12, interleukin-23, interleukin-17 and interferon-γ remain at certain levels (lower than those in Crohn's disease, another inflammatory bowel disease).Long-term exposure to these proinflammatory components, causes mucosal tissue damage persistently, leading to ulcerative colitis.Our simulation results are qualitatively in agreement with clinical and laboratory measurements, offering novel insight into the disease mechanisms.     

Polymer networks by molecular dynamics simulation: Formation, thermal, structural and mechanical properties

A molecular dynamics simulation method is presented and used in the study of the formation of polymer networks. We study the formation of networks representing the methylene repeating units as united atoms. The network formation is accomplished by cross-linking polymer chains with dedicated functional end groups. The simulations reveal that during the cross-linking process, initially branched molecules are formed before the gel point; approaching the gel point, larger branched entities are formed through integration of smaller branched molecules, and at the gel point a network spanning the simulation box is obtained; beyond the gel point the network continues to grow through the addition of the remaining molecules of the sol phase onto the gel (the network); the final completion of the reaction occurs by intra-network connection of dangling ends onto unsaturated cross-linkers. The conformational properties of the strands in the undeformed network are found to be very similar with the conformational properties of the chains before cross-linking. The uniaxial deformation of the formed networks is investigated and the modulus determined from the stress-strain curves shows reciprocal scaling with the precursor chain length for networks formed from sufficiently large precursor chains (N ≥ 20).     

Hydrogen bonding networks controllable by the substitution position of tetrathiafulvalene on the pyridine ring

Because of the effect of pyridine on the substituent position on the TTF group, TTF derivatives exhibit different assembly structures at the interface, which will be of great significance to the construction of functional nanostructures from the molecular design point of view.     

Efficient Gaussian sample specific network marker discovery and drug enrichment analysis validation

Identifying stable gene markers at an individual level can help to understand the genetic mechanisms of each individual patient and accomplish personalized medicine. In this paper, we propose an efficient framework to identify sample-specific markers. Gene expression data first is transformed to a corresponding likelihood matrix to alleviate inherent noise besides adding population information to each sample. Then those significantly differential genes or gene pairs are further mapped to a STRING network for analysis by assuming that the likelihood of each gene or gene pairs in the control group follows a Gaussian distribution. The proposed method is applied to three benchmark datasets including lung adenocarcinoma, kidney renal clear cell carcinoma, and uterine corpus endometrial carcinoma. It is found that disease gene markers identified by the proposed methods outperform the previous sample-specific network (SSN) method in both subtyping and survival analysis. Furthermore, we exploit the application of the subtype markers in following drug selection. The difference of the enriched drug set may reflect some underlying mechanisms of the subtypes and shed light on selecting appropriate drugs for each cancer subtype.     

Entrapment and release of sodium polystyrene sulfonate (SPS) from calcium alginate gel beads

The release of sodium polystyrene sulfonate (SPS) from calcium alginate hydrogel beads has been studied. It has been shown that the structure of the cross-linked calcium alginate network is of primary importance in the retention and/or release of the SPS. This has been evidenced by studying the influence of Ca²⁺ concentration, molar masses (M_n) and the ratio of mannuronic acid/guluronic acid components. A minimum in the SPS release is observed in relation with the organization of the network structure. Conditions inducing the organization of a strong gel (e.g. high Ca²⁺ concentration for example) are not always related to a low release. A good control of release is found when a compromise between a well-structured hydrogel and sterical consideration of SPS is reached.     

应用反向传播神经网络预测化合物脑血分配系数

选用27种三维结构性质描述符对脑血分配系数预测建立神经网络模型.网络模型选用典型的适合函数逼近的两层结构神经网络对脑血分配系数(lgBB,BB为脑血浓度比)进行预测,计算中采用的模型具有一个双曲正切型激活函数的隐含层和一个线性激活函数的输出层.计算表明,使用小心选择的反向传播神经网络模型对化合物脑血分配系数具有较好的预测能力.     

直链型与支链型疏水缔合水凝胶的机械性能与溶胀行为

以丙烯酰胺(AM)为亲水单体,脂肪醇聚氧乙烯醚丙烯酸酯(AEO-AC-n-m,n为疏水端烷基链碳的数目,m为亲水端PEG链的长度,n,m=13,5;10,5;13,10)为疏水单体,十二烷基硫酸钠(SDS)为表面活性剂,过硫酸钾(KPS)为引发剂,通过胶束聚合制备了3种聚丙烯酰胺-co-脂肪醇聚氧乙烯醚丙烯酸酯(AM-co-AEO-AC)疏水缔合水凝胶.以疏水烷基链为直链的疏水单体AEO-AC-13-5合成的直链型水凝胶的网络结构均匀且强度高,其形态在水中可维持180 d.而以疏水烷基链为支链的疏水单体AEO-AC-10-5与AEO-AC-13-10合成的支链型水凝胶的机械性能较弱,60 d内即溶解于水中.在相同条件下,直链型水凝胶断裂时的最大应力是支链型水凝胶的4~5倍.利用弹性橡胶理论中的新胡克方程计算了直链型和支链型水凝胶的有效交联密度ν0和有效交联点间的分子量Mc.     

Structural and spectroscopic properties of Hexamethylenetetramine cobalt(II) complex: [Co(NCS)2(hmt)2(H2O)2][Co(NCS)2(H2O)4] (H2O)

Synthesis, structure, spectroscopy and thermal properties of complex [Co(NCS)₂(hmt)₂(H₂O)₂][Co(NCS)₂(H₂O)₄] (H₂O) (I), assembled by hexamethylenetetramine and octahedral Co(II) metal ions, are reported. Crystal data for I: F_w 387.34, a=9.020(8), b=12.887(9), c=7.95(1) Å, =96.73(4), β=115.36(5), γ=94.16(4)°, V=820(1) Å³, Z=2, space group=P−1, T=173 K, λ(Mo-K)=0.71070 Å, ρ_calc=1.718567 g cm⁻³, μ=17.44 cm⁻¹, R=0.088, R_w=0.148. An interesting two-dimensional network is assembled via hydrogen bonds through coordinated and free water molecules. The d–d transition energy levels of Co(II) ion are determined by UV–vis spectroscopy and calculated by ligand field theory. The calculated results agree well with experiment ones.