Targeting S1PRs as a Therapeutic Strategy for Inflammatory Bone Loss Diseases—Beyond Regulating S1P Signaling

As G protein coupled receptors, sphingosine-1-phosphate receptors (S1PRs) have recently gained attention for their role in modulating inflammatory bone loss diseases. Notably, in murine studies inhibiting S1PR2 by its specific inhibitor, JTE013, alleviated osteoporosis induced by RANKL and attenuated periodontal alveolar bone loss induced by oral bacterial inflammation. Treatment with a multiple S1PRs modulator, FTY720, also suppressed ovariectomy-induced osteoporosis, collagen or adjuvant-induced arthritis, and apical periodontitis in mice. However, most previous studies and reviews have focused mainly on how S1PRs manipulate S1P signaling pathways, subsequently affecting various diseases. In this review, we summarize the underlying mechanisms associated with JTE013 and FTY720 in modulating inflammatory cytokine release, cell chemotaxis, and osteoclastogenesis, subsequently influencing inflammatory bone loss diseases. Studies from our group and from other labs indicate that S1PRs not only control S1P signaling, they also regulate signaling pathways induced by other stimuli, including bacteria, lipopolysaccharide (LPS), bile acid, receptor activator of nuclear factor κB ligand (RANKL), IL-6, and vitamin D. JTE013 and FTY720 alleviate inflammatory bone loss by decreasing the production of inflammatory cytokines and chemokines, reducing chemotaxis of inflammatory cells from blood circulation to bone and soft tissues, and suppressing RANKL-induced osteoclast formation.     

Distinct Roles of Soluble and Transmembrane Adenylyl Cyclases in the Regulation of Flagellar Motility in Ciona Sperm

Adenylyl cyclase (AC) is a key enzyme that synthesizes cyclic AMP (cAMP) at the onset of the signaling pathway to activate sperm motility. Here, we showed that both transmembrane AC (tmAC) and soluble AC (sAC) are distinctly involved in the regulation of sperm motility in the ascidian Ciona intestinalis. A tmAC inhibitor blocked both cAMP synthesis and the activation of sperm motility induced by the egg factor sperm activating and attracting factor (SAAF), as well as those induced by theophylline, an inhibitor of phoshodiesterase. It also significantly inhibited cAMP-dependent phosphorylation of a set of proteins at motility activation. On the other hand, a sAC inhibitor does not affect on SAAF-induced transient increase of cAMP, motility activation or protein phosphorylation, but it reduced swimming velocity to half in theophylline-induced sperm. A sAC inhibitor KH-7 induced circular swimming trajectory with smaller diameter and significantly suppressed chemotaxis of sperm to SAAF. These results suggest that tmAC is involved in the basic mechanism for motility activation through cAMP-dependent protein phosphorylation, whereas sAC plays distinct roles in increase of flagellar beat frequency and in the Ca²⁺-dependent chemotactic movement of sperm.     

Bacterial communication systems: A mathematical formulation of negative chemotaxis

The emergence of molecular communication (MC) has provided a new paradigm for communication at nanoscale, besides the electromagnetic one. Numerous biological systems have been proposed that could be used for communication, using mostly bacteria as information carriers, ensuring biocompatibility and low complexity requirements. In this work, message dissemination dynamics in a bacterial communication system was under investigation by means of a simulation framework that was designed and developed based on a commercial tool. A mathematical formulation is proposed, in an effort to accurately predict the system's behavior under the presence of chemotactic‐like nodes. Simulation results are in strong agreement with the respective mathematical model, for a wide range of biological processes, including phenomena such as chemotaxis, bacterial growth cycle, and biological message transformation dynamics. In the case of a simple simulation scenario exhibiting chemotaxis, the mean accuracy improvement reaches values of up to 19% .     

基于改进粒子群算法的热工温度模型辨识

将细菌趋化、混沌搜索和模拟退火思想引入标准粒子群算法中,对比分析了细菌趋化粒子群算法、混沌模拟退火粒子群算法和模拟退火粒子群算法的辨识结果,探讨了改进算法的工程应用性问题,并将改进算法应用于单入单出的实验室锅炉温度和多入单出的超超临界锅炉主蒸汽温度模型的辨识中。辨识结果表明:细菌趋化粒子群算法可以很好地反映对象的动态特性,提高了辨识精度,缩短了辨识时间,改进了辨识效果。     

基于细菌群体趋药性的有序盲信号分离算法

提出了一种基于细菌趋药性的细菌群优化算法。将探测判断策略和优势细菌随机扰动策略引入细菌群体的进化过程,解决了细菌个体在进化后期处于随机摄动状态而难以定位于全局最优位置的问题。通过使用测试函数对算法性能进行测试以及同其他算法的比较表明,所提出的算法在收敛速度和求解质量方面均有很好的性能。进一步将细菌群优化算法应用于解决盲信号分离问题,实现了对源信号的逐一有序盲分离。仿真实验表明,基于细菌群优化算法的盲信号分离算法具有很好的分离效果,可以将源信号按照其规范四阶累积量绝对值的降序进行有效分离。     

Decoding the Chemical Language of Motile Bacteria by Using High‐Throughput Microfluidic Assays

Motile bacteria navigate chemical environments by using chemoreceptors. The output of these protein sensors is linked to motility machinery and enables bacteria to follow chemical gradients. Understanding the chemical specificity of different families of chemoreceptors is essential for predicting and controlling bacterial behavior in ecological niches, including symbiotic and pathogenic interactions with plants and mammals. The identification of chemical(s) recognized by specific families of receptors is limited by the low throughput and complexity of chemotaxis assays. To address this challenge, we developed a microfluidic‐based chemotaxis assay that is quantitative, simple, and enables high‐throughput measurements of bacterial response to different chemicals. Using the model bacterium Escherichia coli, we demonstrated a strategy for identifying molecules that activate chemoreceptors from a diverse compound library and for determining how global behavioral strategies are tuned to chemical environments.     

A mathematical model of adult subventricular neurogenesis

Neurogenesis has been the subject of active research in recent years and many authors have explored the phenomenology of the process, its regulation and its purported purpose. Recent developments in bioluminescent imaging (BLI) allow direct in vivo imaging of neurogenesis, and in order to interpret the experimental results, mathematical models are necessary. This study proposes such a mathematical model that describes adult mammalian neurogenesis occurring in the subventricular zone and the subsequent migration of cells through the rostral migratory stream to the olfactory bulb (OB). This model assumes that a single chemoattractant is responsible for cell migration, secreted both by the OB and in an endocrine fashion by the cells involved in neurogenesis. The solutions to the system of partial differential equations are compared with the physiological rodent process, as previously documented in the literature and quantified through the use of BLI, and a parameter space is described, the corresponding solution to which matches that of the rodent model. A sensitivity analysis shows that this parameter space is stable to perturbation and furthermore that the system as a whole is sloppy. A large number of parameter sets are stochastically generated, and it is found that parameter spaces corresponding to physiologically plausible solutions generally obey constraints similar to the conditions reported in vivo. This further corroborates the model and its underlying assumptions based on the current understanding of the investigated phenomenon. Concomitantly, this leaves room for further quantitative predictions pertinent to the design of future proposed experiments.     

Biocharts: a visual formalism for complex biological systems

We address one of the central issues in devising languages, methods and tools for the modelling and analysis of complex biological systems, that of linking high-level (e.g. intercellular) information with lower-level (e.g. intracellular) information. Adequate ways of dealing with this issue are crucial for understanding biological networks and pathways, which typically contain huge amounts of data that continue to grow as our knowledge and understanding of a system increases. Trying to comprehend such data using the standard methods currently in use is often virtually impossible. We propose a two-tier compound visual language, which we call Biocharts, that is geared towards building fully executable models of biological systems. One of the main goals of our approach is to enable biologists to actively participate in the computational modelling effort, in a natural way. The high-level part of our language is a version of statecharts, which have been shown to be extremely successful in software and systems engineering. The statecharts can be combined with any appropriately well-defined language (preferably a diagrammatic one) for specifying the low-level dynamics of the pathways and networks. We illustrate the language and our general modelling approach using the well-studied process of bacterial chemotaxis.     

基于均匀设计的改进细菌群体趋药性算法

针对细菌群体趋药性算法（BCC）求解效率较低的问题,提出一种改进的BCC算法。利用均匀设计方法生成初始菌群,使初始菌群在解空间中足够均匀,以充分利用解空间的信息。在细菌间的协作模式框架下,对单点细菌向群体中心点移动方式进行改进,即单个细菌向其群体间最优点的邻域内移动时,为找到潜在位置中的较好解,对潜在位置之间的距离进行等分,以这些等分点中的最优点作为该细菌下一步将要移动到的位置。通过函数优化进行仿真实验,表明改进后的算法在进化代数和寻优成功率上都有较大的提高,具有较高的运行性能。