The Optimal Solution of a Non-Convex State-Dependent LQR Problem and Its Applications

This paper studies a Non-convex State-dependent Linear Quadratic Regulator (NSLQR) problem, in which the control penalty weighting matrix in the performance index is state-dependent. A necessary and sufficient condition for the optimal solution is established with a rigorous proof by Euler-Lagrange Equation. It is found that the optimal solution of the NSLQR problem can be obtained by solving a Pseudo-Differential-Riccati-Equation (PDRE) simultaneously with the closed-loop system equation. A Comparison Theorem for the PDRE is given to facilitate solution methods for the PDRE. A linear time-variant system is employed as an example in simulation to verify the proposed optimal solution. As a non-trivial application, a goal pursuit process in psychology is modeled as a NSLQR problem and two typical goal pursuit behaviors found in human and animals are reproduced using different control weighting . It is found that these two behaviors save control energy and cause less stress over Conventional Control Behavior typified by the LQR control with a constant control weighting , in situations where only the goal discrepancy at the terminal time is of concern, such as in Marathon races and target hitting missions.     

Tampering with cancer chemoresistance by targeting the TGM2-IL6-autophagy regulatory network

Macroautophagy/autophagy is a well-established process involved in maintaining cellular homeostasis, but its role in cancer is complex and even controversial. Many studies have reported a correlative relationship between increased autophagy and evolving cancer cells under stress conditions such as nutrient or oxygen deprivation; however, there has been a lack of a plausible mechanistic link to properly target the autophagy process in the context of this microenvironment. We recently unveiled a positive regulatory loop involving TGM2 (transglutaminase 2)-NFKB/NF-κB signaling, IL6 and autophagy in cancer using mantle cell lymphoma (MCL) as a model system. These pathways are functionally connected to each other, thereby promoting malignant B cell survival and leading to enhanced lymphoma progression both in mice and in patients. Disruption of this network could provide an opportunity to increase the efficacies of current therapies and to reduce MCL drug resistance.     

荒漠灌丛土壤动物分布及其生态功能

在干旱、半干旱荒漠生态系统中,灌丛作为一种重要的植被类型,其独特的形态和生理适应特性能够有效促进退化生态系统结构与功能的恢复。土壤动物是荒漠生态系统中不可或缺的重要组成部分,对促进灌丛"肥岛"演变具有重要的生态作用,有利于灌丛生态功能的发挥及退化生态系统的恢复。近年来,国内外学者对荒漠灌丛微生境土壤动物的研究逐步深入,取得大量的研究成果。在此基础上,首先综述荒漠灌丛微生境土壤动物群落分布和生态功能,总结灌丛与土壤动物分布间作用关系的数学模型,针对荒漠灌丛土壤动物研究中存在的问题提出了未来可能的研究方向和建议。     

Methylation of KvDMR1 involved in regulating the imprinting of CDKN1C gene in cattle

The CDKN1C gene encodes a cyclin‐dependent kinase inhibitor and is one of the key genes involved in the development of Beckwith–Wiedemann syndrome and cancer. In this study, using a direct sequencing approach based on a single nucleotide polymorphism (SNP) at genomic DNA and cDNA levels, we show that CDKN1C exhibits monoallelic expression in all seven studied organs (heart, liver, spleen, lung, kidney, muscle and subcutaneous fat) in cattle. To investigate how methylation regulates imprinting of CDKN1C in cattle, allele‐specific methylation patterns in two putative differential methylation regions (DMRs), the CDKN1C DMR and KvDMR1, were analyzed in three tissues (liver, spleen and lung) using bisulfite sequencing PCR. Our results show that in the CDKN1C DMR both parental alleles were unmethylated in all three analyzed tissues. In contrast, KvDMR1 was differentially methylated between the two parental alleles in the same tissues. Statistical analysis showed that there is a significant difference in the methylation level between the two parental alleles (P < 0.01), confirming that this region is the DMR of KvDMR1 and that it may be correlated with CDKN1C imprinting.