Anti-periodic solution for fuzzy Cohen–Grossberg neural networks with time-varying and distributed delays

In this paper, by using a continuation theorem of coincidence degree theory and a differential inequality, we establish some sufficient conditions ensuring the existence and global exponential stability of anti-periodic solutions for a class of fuzzy Cohen–Grossberg neural networks with time-varying and distributed delays. In addition, we present an illustrative example to show the feasibility of obtained results

Existence and Global Exponential Stability of Almost Periodic Solutions for a Class of Delay Duffing Equations on Time Scales

Based on the exponential dichotomy of linear dynamic equations on time scales, we obtain some sufficient conditions for the existence and global exponential stability of almost periodic solutions for a class of Duffing equations with time-varying delays on time scales. We also present numerical examples to show the feasibility of obtained results. The results of this paper are completely new even when the time scale T = R or Z and are complementary to the previously known results

Yarrowia lipolytica: A versatile microbial workhorse for expanding nature’s biosynthetic capacity

Yarrowia lipolytica is an oleaginous yeast that have been substantially engineered for production of oleochemcials and drop-in transportation fuels. It has been considered as a ‘generally recognized as safe’ (GRAS) organism for the production of organic acids in the food and nutraceutical industry. The high precursor acetyl-CoA and malonyl-CoA flux along with the versatile carbon-utilization capability makes this yeast as a superior host to upgrade low-value carbons into high-value pharmaceuticals and plant natural products (PNPs). Bacteria system in general is less efficient to express the complex gene cluster of plant natural product pathway. Unlike bacteria, yeast has developed spatially separated organelles to partition specialized metabolic functions into distinct cellular compartments. In this talk, we will present strategies to harness the endogenous acetyl-CoA/malonyl-CoA/HMG-CoA metabolism toward engineering efficient yeast cell factories to produce complex oleochemicals, terpenes, polyketides and aromatic commodity chemicals. We identified pathway limitations and assessed genetic engineering strategies to elevate the level of acetyl-CoA, malonyl-CoA, HMG-CoA and NADPH. This work will provide a testbed for engineering Y. lipolytica and expanding nature’s biosynthetic capacity to produce complex fuels and chemicals from renewable feedstocks

Disturbance observer-based neural network control of cooperative multiple manipulators with input saturation

In this paper, the complex problems of internal forces and position control are studied simultaneously and a disturbance observer-based radial basis function neural network (RBFNN) control scheme is proposed to: 1) estimate the unknown parameters accurately; 2) approximate the disturbance experienced by the system due to input saturation; and 3) simultaneously improve the robustness of the system. More specifically, the proposed scheme utilizes disturbance observers, neural network (NN) collaborative control with an adaptive law, and full state feedback. Utilizing Lyapunov stability principles, it is shown that semiglobally uniformly bounded stability is guaranteed for all controlled signals of the closed-loop system. The effectiveness of the proposed controller as predicted by the theoretical analysis is verified by comparative experimental studies

Existence and Exponential Stability of Equilibrium Point for Fuzzy BAM Neural Networks with Infinitely Distributed Delays and Impulses on Time Scales

By using the fixed point theorem and constructing a Lyapunov functional, we establish some sufficient conditions on the existence, uniqueness, and exponential stability of equilibrium point for a class of fuzzy BAM neural networks with infinitely distributed delays and impulses on time scales. We also present a numerical example to show the feasibility of obtained results. Our example also shows that the described time and continuous neural time networks have the same dynamic behaviours for the stability

Investigation of lipid metabolism dysregulation and the effects on immune microenvironments in pan-cancer using multiple omics data.

BACKGROUND: Lipid metabolism reprogramming is a hallmark for tumor which contributes to tumorigenesis and progression, but the commonality and difference of lipid metabolism among pan-cancer is not fully investigated. Increasing evidences suggest that the alterations in tumor metabolism, including metabolite abundance and accumulation of metabolic products, lead to local immunosuppression in the tumor microenvironment. An integrated analysis of lipid metabolism in cancers from different tissues using multiple omics data may provide novel insight into the understanding of tumorigenesis and progression. RESULTS: Through systematic analysis of the multiple omics data from TCGA, we found that the most-widely altered lipid metabolism pathways in pan-cancer are fatty acid metabolism, arachidonic acid metabolism, cholesterol metabolism and PPAR signaling. Gene expression profiles of fatty acid metabolism show commonalities across pan-cancer, while the alteration in cholesterol metabolism and arachidonic acid metabolism differ with tissue origin, suggesting tissue specific lipid metabolism features in different tumor types. An integrated analysis of gene expression, DNA methylation and mutations revealed factors that regulate gene expression, including the differentially methylated sites and mutations of the lipid genes, as well as mutation and differential expression of the up-stream transcription factors for the lipid metabolism pathways. Correlation analysis of the proportion of immune cells in the tumor microenvironment and the expression of lipid metabolism genes revealed immune-related differentially expressed lipid metabolic genes, indicating the potential crosstalk between lipid metabolism and immune response. Genes related to lipid metabolism and immune response that are associated with poor prognosis were discovered including HMGCS2, GPX2 and CD36, which may provide clues for tumor biomarkers or therapeutic targets. CONCLUSIONS: Our study provides an integrated analysis of lipid metabolism in pan-cancer, highlights the perturbation of key metabolism processes in tumorigenesis and clarificates the regulation mechanism of abnormal lipid metabolism and effects of lipid metabolism on tumor immune microenvironment. This study also provides new clues for biomarkers or therapeutic targets of lipid metabolism in tumors

Paper-based microfluidics for rapid diagnostics and drug delivery

Paper is a common material that is promising for constructing microfluidic chips (lab-on-a-paper) for diagnostics and drug delivery for biomedical applications. In the past decade, extensive research on paper-based microfluidics has accumulated a large number of scientific publications in the fields of biomedical diagnosis, food safety, environmental health, drug screening and delivery. This review focuses on the recent progress on paper-based microfluidic technology with an emphasis on the design, optimization and application of the technology platform, in particular for medical diagnostics and drug delivery. Novel advances have concentrated on engineering paper devices for point-of-care (POC) diagnostics, which could be integrated with nucleic acid-based tests and isothermal amplification experiments, enabling rapid sample-to-answer assays for field testing. Among the isothermal amplification experiments, loop-mediated isothermal amplification (LAMP), an extremely sensitive nucleic acid test, specifically identifies ultralow concentrations of DNA/RNA from practical samples for diagnosing diseases. We thus mainly focus on the paper device-based LAMP assay for the rapid infectious disease diagnosis, foodborne pathogen analysis, veterinary diagnosis, plant diagnosis, and environmental public health evaluation. We also outlined progress on paper microfluidic devices for drug delivery. The paper concludes with a discussion on the challenges of this technology and our insights into how to advance science and technology towards the development of fully functional paper devices in diagnostics and drug delivery