Insights into the molecular mechanisms of bacterial metabolites in the pathogenesis of autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder usually diagnosed at early age and characterized by impairments in social behavior and communication, the presence of repetitive behavior, and deficits in learning and memory. Two of these bacterial metabolites, p-cresol sulfate (pCS) and 4-ethylphenyl sulfate (4EPS), are reported to be enhanced in feces, blood and urine of people diagnosed with ASD. Moreover, pCS and 4EPS exposure in mice induces ASD-like behavior, but the exact underlying mechanisms remain to be investigated. Many sheddases are members of the so-called ADAM family and potentially play a role in the pathogenesis of disease. In addition, the phosphatase PTEN is an important enzyme that regulates neural cell growth and survival in the brain. This thesis is focused on gaining insights into the possible molecular mechanisms of bacterial metabolites in the pathogenesis of ASD to identify potential new targets for intervention and therapy. Using an ASD mouse model and a neuroinflammation cell model, this thesis illustrates that pCS and 4EPS affect the level and function of the sheddases, ADAM10 & ADAM17, and the phosphatase, PTEN, that might be involved in the ASD-associated changes in neuroimmune responses and/or neuronal network function in the brain. In addition, this thesis further identifies that ADAM10 might be a treatment-target for ASD either through direct pharmacological inhibition or via nutritional interventions targeting bacteria that are involved in pCS and 4EPS production aimed to reduce ASD-associated detrimental symptoms

Joint Computing Offloading and Resource Allocation for Classification Intelligent Tasks in MEC Systems

Mobile edge computing (MEC) enables low-latency and high-bandwidth applications by bringing computation and data storage closer to end-users. Intelligent computing is an important application of MEC, where computing resources are used to solve intelligent task-related problems based on task requirements. However, efficiently offloading computing and allocating resources for intelligent tasks in MEC systems is a challenging problem due to complex interactions between task requirements and MEC resources. To address this challenge, we investigate joint computing offloading and resource allocation for intelligent tasks in MEC systems. Our goal is to optimize system utility by jointly considering computing accuracy and task delay to achieve maximum system performance. We focus on classification intelligence tasks and formulate an optimization problem that considers both the accuracy requirements of tasks and the parallel computing capabilities of MEC systems. To solve the optimization problem, we decompose it into three subproblems: subcarrier allocation, computing capacity allocation, and compression offloading. We use convex optimization and successive convex approximation to derive closed-form expressions for the subcarrier allocation, offloading decisions, computing capacity, and compressed ratio. Based on our solutions, we design an efficient computing offloading and resource allocation algorithm for intelligent tasks in MEC systems. Our simulation results demonstrate that our proposed algorithm significantly improves the performance of intelligent tasks in MEC systems and achieves a flexible trade-off between system revenue and cost considering intelligent tasks compared with the benchmarks.Comment: arXiv admin note: substantial text overlap with arXiv:2307.0274

Preliminary study of regulation technology of wind field distribution on QTT site based on test of equivalent wind field

The effect of wind gust on the large reflector antenna is one of the main factors that can affect the antenna performance and therefore, this effect must be minimized to meet the strict performance requirement in the world largest steerable telescope, which is QiTai Telescope (QTT). In this paper, the characteristics of the topography as well as the wind distribution around QTT site have been analyzed and consequently, a technology for improving the wind distribution in an active way has been proposed. Additionally, an equivalent wind distribution test rig for the proposed technology has been built in the lab and the corresponding experiment has been carried out. The experimental data indicated that the proposed technology was a promising tool for regulating the wind distribution for the large reflector antenna and it was found that the proposed technology can significantly reduce the wind speed as well as the wind impact range after the wind regulation has been given in the test. The results in this paper has provided a solid foundation for the regulation of the wind distribution of the QTT site

Bioelectricity generation from the decolorization of reactive blue 19 by using microbial fuel cell.

Microbial fuel cell (MFC) was compared to conventional biological techniques for decolorization of anthraquinone dye, reactive blue 19 (RB19) with simultaneous electricity generation. With 50 mg/L of RB19 in the anode chamber as a fuel, the MFC achieved 89% decolorization efficiency of RB19 within 48 h, compared with 51 and 55% decolorization efficiency achieved by aerobic and anaerobic techniques, respectively. The cyclic voltammetry results showed that RB19 could promote the electron transfer and redox reaction on the surface of anode. The RB19 decolorization process can be described by first-order kinetics, and the decolorization rate decreased with the increase of RB19 concentration. The high-throughput 16S rRNA sequencing analysis indicated significant microbial community shift in the MFC. At phylum level, the majority of sequences belong to Proteobacteria, accounting from 23 to 84% of the total reads in each bacterium community. At genus level, the MFC contained two types of microorganisms in general such as electrochemically active and decolorization bacteria. Overall, MFC is an effective method for anthraquinone dye treatment with simultaneous energy recovery. The 16S rRNA revealed that there were two major functioning microbial communities in the MFC such as electricity-producing and RB19-degrading bacteria which synergistically worked on RB19 degradation

The Autism Spectrum Disorder-Associated Bacterial Metabolite p-Cresol Derails the Neuroimmune Response of Microglial Cells Partially via Reduction of ADAM17 and ADAM10.

The bacterial metabolite 4-methylphenol ( para-cresol or p-cresol) and its derivative p-cresyl sulfate ( pCS) are elevated in the urine and feces of children with autism spectrum disorder (ASD). It has been shown that p-cresol administration induces social behavior deficits and repetitive behavior in mice. However, the mechanisms of p-cresol, specifically its metabolite pCS that can reach the brain, in ASD remain to be investigated. The pCS has been shown to inhibit LPS-stimulated inflammatory response. A Disintegrin And Metalloprotease 10 (ADAM10) and A Disintegrin And Metalloprotease 17 (ADAM17) are thought to regulate microglial immune response by cleaving membrane-bound proteins. In the present study, a neuroinflammation model of LPS-activated BV2 microglia has been used to unveil the potential molecular mechanism of pCS in ASD pathogenesis. In microglial cells pCS treatment decreases the expression or maturation of ADAM10 and ADAM17. In addition, pCS treatment attenuates TNF-α and IL-6 releases as well as phagocytosis activity of microglia. In in vitro ADAM10/17 inhibition experiments, either ADAM10 or ADAM17 inhibition reduces constitutive and LPS-activated release of TNF-α, TNFR-1 and IL-6R by microglial cells, while it increases constitutive and LPS-activated microglial phagocytotic activity. The in vivo results further confirm the involvement of ADAM10 and ADAM17 in ASD pathogenesis. In in utero VPA-exposed male mice, elevated concentration in serum of p-cresol-associated metabolites pCS and p-cresyl glucuronide ( pCG) is associated with a VPA-induced increased ADAM10 maturation, and a decreased ADAM17 maturation that is related with attenuated levels of soluble TNF-α and TGF-β1 in the mice brain. Overall, the present study demonstrates a partial role of ADAM10 and ADAM17 in the derailed innate immune response of microglial cells associated with pCS-induced ASD pathogenesis

The Effect of Recycling Flux on the Performance and Microbial Community Composition of a Biofilm Hydrolytic-Aerobic Recycling Process Treating Anthraquinone Reactive Dyes

Synthetic dyes are extensively used and rarely degraded. Microbial decomposition is a cost-effective alternative to chemical and physical degradation processes. In this study, the decomposition of simulated anthraquinone reactive dye (Reactive Blue 19; RB19) at a concentration of 400-mg/L in wastewater by a biofilm hydrolytic-aerobic recycling system was investigated over a range of recycling fluxes. The 16S rDNA-based fingerprint technique was also used to investigate the microbial community composition. Results indicated that the recycling flux was a key factor that influenced RB19 degradation. The RB19 and COD removal efficiency could reach values as high as 82.1% and 95.4%, respectively, with a recycling flux of 10 mL/min. Molecular analysis indicated that some strains were similar to Aeromonadales, Tolumonas, and some uncultured clones were assumed to be potential decolorization bacteria. However, the microbial community composition in the reactors remained relatively stable at different recycling fluxes. This study provided insights on the decolorization capability and the population dynamics during the decolorization process of anthraquinone dye wastewater.National Natural Science Foundation of China[40801195, 41071302]; State Key Lab of Urban Water Resource and Environment (HIT)[QA200809

The diagnostic analysis of the fault coupling effects in planet bearing

The purpose of this paper is to investigate the fault coupling effects in the planet bearing as well as the corresponding vibration signatures in the resultant vibration spectrum. In a planetary gear application, the planet bearing can not only spin around the planet gear axis, but also revolve about the sun gear axis and this rotating mechanism poses a big challenge for the diagnostic analysis of the planet bearing vibration spectrum. In addition, the frequency component interaction and overlap phenomenon in the vibration spectrum caused by the fault coupling effect can even worsen the diagnosis results. To further the understanding of the fault coupling effects in a planet bearing, a 34° of freedom planetary gear model with detailed planet bearing model was established to obtain the dynamic response in the presence of various bearing fault scenarios. The method of modelling the bearing distributed faults and localized faults has been introduced in this paper, which can be further incorporated into the planetary gear model to obtain the faulted vibration signal. The “benchmark” method has been adopted to enhance the planet bearing fault impulses in the vibration signals and in total, the amplitude demodulation results from 20 planet bearing fault scenarios have been investigated and analyzed. The coherence estimation over the vibration frequency domain has been proposed as a tool to quantify the fault impact contribution from different fault modes and the results suggested that the outer raceway fault contributes most to the resultant planet bearing vibration spectrum in all the investigated fault scenarios

A community challenge for a pancancer drug mechanism of action inference from perturbational profile data

The Columbia Cancer Target Discovery and Development (CTD2) Center is developing PANACEA, a resource comprising dose-responses and RNA sequencing (RNA-seq) profiles of 25 cell lines perturbed with similar to 400 clinical oncology drugs, to study a tumor-specific drug mechanism of action. Here, this resource serves as the basis for a DREAM Challenge assessing the accuracy and sensitivity of computational algorithms for de novo drug polypharmacology predictions. Dose-response and perturbational profiles for 32 kinase inhibitors are provided to 21 teams who are blind to the identity of the compounds. The teams are asked to predict high-affinity binding targets of each compound among similar to 1,300 targets cataloged in DrugBank. The best performing methods leverage gene expression profile similarity analysis as well as deep-learning methodologies trained on individual datasets. This study lays the foundation for future integrative analyses of pharmacogenomic data, reconciliation of polypharmacology effects in different tumor contexts, and insights into network-based assessments of drug mechanisms of action.Peer reviewe

A Novel Approach to Molecular Recognition Surface of Magnetic Nanoparticles Based on Host–Guest Effect

A novel route has been developed to prepared β-cyclodextrin (β-CD) functionalized magnetic nanoparticles (MNPs). The MNPs were first modified with monotosyl-poly(ethylene glycol) (PEG) silane and then tosyl units were displaced by amino-β-CD through the nucleophilic substitution reaction. The monotosyl-PEG silane was synthesized by modifying a PEG diol to form the corresponding monotosyl-PEG, followed by a reaction with 3-isocyanatopropyltriethoxysilane (IPTS). The success of the synthesis of the monotosyl-PEG silane was confirmed with1H NMR and Fourier transform infrared (FTIR) spectroscopy. The analysis of FTIR spectroscopy and X-ray photoelectron spectroscopy (XPS) confirmed the immobilization of β-CD onto MNPs. Transmission electron microscopy (TEM) indicated that the β-CD functionalized MNPs were mostly present as individual nonclustered units in water. The number of β-CD molecules immobilized on each MNP was about 240 according to the thermogravimetric analysis (TGA) results. The as-prepared β-CD functionalized MNPs were used to detect dopamine with the assistance of a magnet