Brain regions show different metabolic and protein arginine methylation phenotypes in frontotemporal dementias and Alzheimer's disease

Frontotemporal dementia (FTD) is a heterogeneous neurodegenerative disease with multiple histopathological subtypes. FTD patients share similar symptoms with Alzheimer's disease (AD). Hence, FTD patients are commonly misdiagnosed as AD, despite the consensus clinical diagnostic criteria. It is therefore of great clinical need to identify a biomarker that can distinguish FTD from AD and control individuals, and potentially further differentiate between FTD pathological subtypes. We conducted a metabolomic analysis on post-mortem human brain tissue from three regions: cerebellum, frontal cortex and occipital cortex from control, FTLD-TDP type A, type A-C9, type C and AD. Our results indicate that the brain subdivisions responsible for different functions show different metabolic patterns. We further explored the region-specific metabolic characteristics of different FTD subtypes and AD patients. Different FTD subtypes and AD share similar metabolic phenotypes in the cerebellum, but AD exhibited distinct metabolic patterns in the frontal and occipital regions compared to FTD. The identified brain region-specific metabolite biomarkers could provide a tool for distinguishing different FTD subtypes and AD and provide the first insights into the metabolic changes of FTLD-TDP type A, type A-C9, type C and AD in different regions of the brain. The importance of protein arginine methylation in neurodegenerative disease has come to light, so we investigated whether the arginine methylation level contributes to disease pathogenesis. Our findings provide new insights into the relationship between arginine methylation and metabolic changes in FTD subtypes and AD that could be further explored, to study the molecular mechanism of pathogenesis

BOIN: An R Package for Designing Single-Agent and Drug-Combination Dose-Finding Trials Using Bayesian Optimal Interval Designs

This article describes the R package BOIN, which implements a recently developed methodology for designing single-agent and drug-combination dose-finding clinical trials using Bayesian optimal interval designs (Liu and Yuan 2015; Yuan, Hess, Hilsenbeck, and Gilbert 2016). The BOIN designs are novel "model-assisted" phase I trial designs that can be implemented simply and transparently, similar to the 3 + 3 design, but yield excellent performance comparable to those of more complicated, model-based designs. The BOIN package provides tools for designing, conducting, and analyzing single-agent and drug-combination dose-finding trials

Phosphorylation Regulates CIRBP Arginine Methylation, Transportin-1 Binding and Liquid-Liquid Phase Separation

Arginine-glycine(-glycine) (RG/RGG) regions are highly abundant in RNA-binding proteins and involved in numerous physiological processes. Aberrant liquid-liquid phase separation (LLPS) and stress granule (SGs) association of RG/RGG regions in the cytoplasm have been implicated in several neurodegenerative disorders. LLPS and SG association of these proteins is regulated by the interaction with nuclear import receptors, such as transportin-1 (TNPO1), and by post-translational arginine methylation. Strikingly, many RG/RGG proteins harbour potential phosphorylation sites within or close to their arginine methylated regions, indicating a regulatory role. Here, we studied the role of phosphorylation within RG/RGG regions on arginine methylation, TNPO1-binding and LLPS using the cold-inducible RNA-binding protein (CIRBP) as a paradigm. We show that the RG/RGG region of CIRBP is in vitro phosphorylated by serine-arginine protein kinase 1 (SRPK1), and discovered two novel phosphorylation sites in CIRBP. SRPK1-mediated phosphorylation of the CIRBP RG/RGG region impairs LLPS and binding to TNPO1 in vitro and interferes with SG association in cells. Furthermore, we uncovered that arginine methylation of the CIRBP RG/RGG region regulates in vitro phosphorylation by SRPK1. In conclusion, our findings indicate that LLPS and TNPO1-mediated chaperoning of RG/RGG proteins is regulated through an intricate interplay of post-translational modifications

Cattle Mammary Bioreactor Generated by a Novel Procedure of Transgenic Cloning for Large-Scale Production of Functional Human Lactoferrin

Large-scale production of biopharmaceuticals by current bioreactor techniques is limited by low transgenic efficiency and low expression of foreign proteins. In general, a bacterial artificial chromosome (BAC) harboring most regulatory elements is capable of overcoming the limitations, but transferring BAC into donor cells is difficult. We describe here the use of cattle mammary bioreactor to produce functional recombinant human lactoferrin (rhLF) by a novel procedure of transgenic cloning, which employs microinjection to generate transgenic somatic cells as donor cells. Bovine fibroblast cells were co-microinjected for the first time with a 150-kb BAC carrying the human lactoferrin gene and a marker gene. The resulting transfection efficiency of up to 15.79×10−2 percent was notably higher than that of electroporation and lipofection. Following somatic cell nuclear transfer, we obtained two transgenic cows that secreted rhLF at high levels, 2.5 g/l and 3.4 g/l, respectively. The rhLF had a similar pattern of glycosylation and proteolytic susceptibility as the natural human counterpart. Biochemical analysis revealed that the iron-binding and releasing properties of rhLF were identical to that of native hLF. Importantly, an antibacterial experiment further demonstrated that rhLF was functional. Our results indicate that co-microinjection with a BAC and a marker gene into donor cells for somatic cell cloning indeed improves transgenic efficiency. Moreover, the cattle mammary bioreactors generated with this novel procedure produce functional rhLF on an industrial scale

Approche moleculaire de la caracterisation de trois alterations chromosomiques observees en pathologie tumorale ou constitutionnelle

SIGLEINIST T 74029 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Analysis of the Influence of Heterogeneous Environmental Regulation on Green Technology Innovation

Since its reform and opening up, China’s economy has undergone rapid development and has experienced problems such as the overexploitation of resources and the destruction of the ecological environment. To achieve a balance between economic growth and environmental protection and to follow the sustainable development path, China must implement corresponding environmental regulation policies and vigorously encourage enterprises to pursue green technology innovation. In this paper, environmental regulation is divided into command-and-control, market incentive and voluntary participation. Command-and-control environmental regulation is measured using the entropy method and the logarithm of the pollution discharge fee income in each region is used as the measurement index of market-incentive environmental regulations. At the same time, the logarithm of the number of environmental protection proposals planned by the National People’s Congress and the number of environmental protection proposals planned by the CPPCC is used as the measurement index of voluntary participation in environmental regulations. Based on a regression equation of the effects of environmental regulations on green technology innovation, this paper uses the two-step system GMM method to analyze the panel data of industrial enterprises larger than a designated size in 30 provinces, autonomous regions and municipalities in China from 2006 to 2017. Moreover, the paper compares the effects of command-and-control, market-incentive and voluntary participatory environmental regulations on green technology innovation. The empirical results show that command-and-control environmental regulations initially have an inverted U-shaped effect on green technology innovation and market incentive and voluntary participatory environmental regulations have a U-shaped effect on green technology innovation. A comparison of the three environmental regulation policies shows that the effect of command-and-control environmental regulation is more significant

Metabolic Regulation of Hepatitis B Virus Infection in HBV-Transgenic Mice

Hepatitis B virus (HBV) infection is a worldwide health burden. Metabolomics analysis has revealed HBV-induced metabolism dysregulation in liver tissues and hepatocytes. However, as an infectious disease, the tissue-specific landscape of metabolic profiles of HBV infection remains unclear. To fill this gap, we applied untargeted nuclear magnetic resonance (NMR) metabolomic analysis of the heart, liver, spleen, lung, kidney, pancreas, and intestine (duodenum, jejunum, ileum) in HBV-transgenic mice and their wild-type littermates. Strikingly, we found systemic metabolic alterations induced by HBV in liver and extrahepatic organs. Significant changes in metabolites have been observed in most tissues of HBV-transgenic mice, except for ileum. The metabolic changes may provide novel therapeutic targets for the treatment of HBV infection. Moreover, tissue-specific metabolic profiles could speed up the study of HBV induced systemic metabolic reprogramming, which could help follow the progression of HBV infection and explain the underlying pathogenesis

Design of a terahertz metamaterial sensor based on split ring resonator nested square ring resonator

A terahertz (THz) sensor based on the metamaterial structure, split ring resonator with four-gaps relied on centrosymmetric nested square ring resonator, is presented. The two resonant elements of the metamaterial structure generate a corresponding resonant valley on the transmission spectrum curve in the frequency range from 0.1 to 1.9 THz respectively, and both of these resonant valleys show different redshifts when the surface permittivity of the structure changes. This feature is very suitable for THz sensing, especially the quantum interference effect between the two resonant elements, which results in the formation of an electromagnetically induced transparency (EIT)-like resonance peak on the transmission spectrum curve. The sensing performances are simulated by using commercialized full-wave electromagnetic simulation software. The results demonstrated that the proposed sensor is polarization-insensitive and has a highly boosted sensitivity, which has a promising application prospect in the fields of biomedical science and drug industry

Development of an Apparatus for Crop-Growth Monitoring and Diagnosis

To non-destructively acquire leaf nitrogen content (LNC), leaf nitrogen accumulation (LNA), leaf area index (LAI), and leaf dry weight (LDW) data at high speed and low cost, a portable apparatus for crop-growth monitoring and diagnosis (CGMD) was developed according to the spectral monitoring mechanisms of crop growth. According to the canopy characteristics of crops and actual requirements of field operation environments, splitting light beams by using an optical filter and proper structural parameters were determined for the sensors. Meanwhile, an integral-type weak optoelectronic signal processing circuit was designed, which changed the gain of the system and guaranteed the high resolution of the apparatus by automatically adjusting the integration period based on the irradiance received from ambient light. In addition, a coupling processor system for a sensor information and growth model based on the microcontroller chip was developed. Field experiments showed that normalised vegetation index (NDVI) measured separately through the CGMD apparatus and the ASD spectrometer showed a good linear correlation. For measurements of canopy reflectance spectra of rice and wheat, their linear determination coefficients (R2) were 0.95 and 0.92, respectively while the root mean square errors (RMSEs) were 0.02 and 0.03, respectively. NDVI value measured by using the CGMD apparatus and growth indices of rice and wheat exhibited a linear relationship. For the monitoring models for LNC, LNA, LAI, and LDW of rice based on linear fitting of NDVI, R2 were 0.64, 0.67, 0.63 and 0.70, and RMSEs were 0.31, 2.29, 1.15 and 0.05, respectively. In addition, R2 of the models for monitoring LNC, LNA, LAI, and LDW of wheat on the basis of linear fitting of NDVI were 0.82, 0.71, 0.72 and 0.70, and RMSEs were 0.26, 2.30, 1.43, and 0.05, respectively