Preparation and thermal analysis kinetics of the core–nanoshell composite materials doped with Sm

The core–nanoshell composite materials with magnetic fly-ash hollow cenosphere as core and nano SmFeO3 as shell were synthesized by high-energy ball milling method. The magnetic fly-ash hollow cenosphere, samarium nitrate, and iron nitrate were used as raw materials. The synthesis and growth kinetics of the composite materials were investigated using the thermogravimetry and differential thermal analysis (TG–DTA) at different heating rates. The results show that the precursor of the composite materials decomposes in three steps. The apparent activation energy of each stage was calculated using the Doyle–Ozawa and Kissinger methods. The reaction order, frequency factor, and rate equations were also determined. The activation energy of the nano crystallite growth is calculated to be 16.12 kJ mol−1 according to kinetics theory of nano crystallite growth. It can be inferred that the crystallite grows primarily by means of an interfacial reaction during the thermal treatment. The magnetic properties and microwave absorbing properties of samples were analyzed by the vibrating sample magnetometer analysis and vector network analyzer. The results indicated that the exchange coupling interaction happens between ferrite of magnetic fly-ash hollow cenosphere and nanosized ferrite coating, which cause outstanding magnetic properties. In the frequency between 1 MHz and 1 GHz, the absorbing effectiveness of the composite absorbers can achieve −32 dB. The magnetic properties of the composite material are better than those of single phase. So it is consistent with requirements of the microwave absorbing material at the low-frequency absorption.National Natural Science Foundation (China) (No. 20976018)Liaoning Sheng (China) (Science Research Plan Project, Higher Education Department (No. L2013176))China. Ministry of Education (Key Laboratory of Industrial Ecology and Environmental Engineering, KLIEEE-12-03)China. Ministry of Education (National Project of China ‘‘Innovation and Entrepreneurship Training Program of Undergraduate students’’ (201310150002)

BigDataBench: a Big Data Benchmark Suite from Internet Services

As architecture, systems, and data management communities pay greater attention to innovative big data systems and architectures, the pressure of benchmarking and evaluating these systems rises. Considering the broad use of big data systems, big data benchmarks must include diversity of data and workloads. Most of the state-of-the-art big data benchmarking efforts target evaluating specific types of applications or system software stacks, and hence they are not qualified for serving the purposes mentioned above. This paper presents our joint research efforts on this issue with several industrial partners. Our big data benchmark suite BigDataBench not only covers broad application scenarios, but also includes diverse and representative data sets. BigDataBench is publicly available from http://prof.ict.ac.cn/BigDataBench . Also, we comprehensively characterize 19 big data workloads included in BigDataBench with varying data inputs. On a typical state-of-practice processor, Intel Xeon E5645, we have the following observations: First, in comparison with the traditional benchmarks: including PARSEC, HPCC, and SPECCPU, big data applications have very low operation intensity; Second, the volume of data input has non-negligible impact on micro-architecture characteristics, which may impose challenges for simulation-based big data architecture research; Last but not least, corroborating the observations in CloudSuite and DCBench (which use smaller data inputs), we find that the numbers of L1 instruction cache misses per 1000 instructions of the big data applications are higher than in the traditional benchmarks; also, we find that L3 caches are effective for the big data applications, corroborating the observation in DCBench.Comment: 12 pages, 6 figures, The 20th IEEE International Symposium On High Performance Computer Architecture (HPCA-2014), February 15-19, 2014, Orlando, Florida, US

Microbiome-derived bile acids contribute to elevated antigenic response and bone erosion in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic, disabling and incurable autoimmune disease. It has been widely recognized that gut microbial dysbiosis is an important contributor to the pathogenesis of RA, although distinct alterations in microbiota have been associated with this disease. Yet, the metabolites that mediate the impacts of the gut microbiome on RA are less well understood. Here, with microbial profiling and non-targeted metabolomics, we revealed profound yet diverse perturbation of the gut microbiome and metabolome in RA patients in a discovery set. In the Bacteroides-dominated RA patients, differentiation of gut microbiome resulted in distinct bile acid profiles compared to healthy subjects. Predominated Bacteroides species expressing BSH and 7a-HSDH increased, leading to elevated secondary bile acid production in this subgroup of RA patients. Reduced serum fibroblast growth factor-19 and dysregulated bile acids were evidence of impaired farnesoid X receptor-mediated signaling in the patients. This gut microbiota-bile acid axis was correlated to ACPA. The patients from the validation sets demonstrated that ACPA-positive patients have more abundant bacteria expressing BSH and 7a-HSDH but less Clostridium scindens expressing 7a-dehydroxylation enzymes, together with dysregulated microbial bile acid metabolism and more severe bone erosion than ACPA-negative ones. Mediation analyses revealed putative causal relationships between the gut microbiome, bile acids, and ACPA-positive RA, supporting a potential causal effect of Bacteroides species in increasing levels of ACPA and bone erosion mediated via disturbing bile acid metabolism. These results provide insights into the role of gut dysbiosis in RA in a manifestation-specific manner, as well as the functions of bile acids in this gut-joint axis, which may be a potential intervention target for precisely controlling RA conditions.Comment: 38 pages, 6 figure

DeepAIR: A deep learning framework for effective integration of sequence and 3D structure to enable adaptive immune receptor analysis

Structural docking between the adaptive immune receptors (AIRs), including T cell receptors (TCRs) and B cell receptors (BCRs), and their cognate antigens are one of the most fundamental processes in adaptive immunity. However, current methods for predicting AIR-antigen binding largely rely on sequence-derived features of AIRs, omitting the structure features that are essential for binding affinity. In this study, we present a deep learning framework, termed DeepAIR, for the accurate prediction of AIR-antigen binding by integrating both sequence and structure features of AIRs. DeepAIR achieves a Pearson’s correlation of 0.813 in predicting the binding affinity of TCR, and a median area under the receiver-operating characteristic curve (AUC) of 0.904 and 0.942 in predicting the binding reactivity of TCR and BCR, respectively. Meanwhile, using TCR and BCR repertoire, DeepAIR correctly identifies every patient with nasopharyngeal carcinoma and inflammatory bowel disease in test data. Thus, DeepAIR improves the AIR-antigen binding prediction that facilitates the study of adaptive immunity

Neuropathic Injury-Induced Plasticity of GABAergic System in Peripheral Sensory Ganglia

GABA is a major inhibitory neurotransmitter in the mammalian central nervous system (CNS). Inhibitory GABAA channel circuits in the dorsal spinal cord are the gatekeepers of the nociceptive input from the periphery to the CNS. Weakening of these spinal inhibitory mechanisms is a hallmark of chronic pain. Yet, recent studies have suggested the existence of an earlier GABAergic “gate” within the peripheral sensory ganglia. In this study, we performed systematic investigation of plastic changes of the GABA-related proteins in the dorsal root ganglion (DRG) in the process of neuropathic pain development. We found that chronic constriction injury (CCI) induced general downregulation of most GABAA channel subunits and the GABA-producing enzyme, glutamate decarboxylase, consistent with the weakening of the GABAergic inhibition at the periphery. Strikingly, the α5 GABAA subunit was consistently upregulated. Knock-down of the α5 subunit in vivo moderately alleviated neuropathic hyperalgesia. Our findings suggest that while the development of neuropathic pain is generally accompanied by weakening of the peripheral GABAergic system, the α5 GABAA subunit may have a unique pro-algesic role and, hence, might represent a new therapeutic target

An improved extraction method reveals varied DNA content in different parts of the shells of Pacific oysters

The DNA in the shell of Crassostrea gigas could have important roles in the shell biomineralization. However, limited by the low efficiency of existing extraction methods, studies investigating the DNA in shells are lacking. In this study, the shell DNA of C. gigas was extracted using the organic solvent extraction (OSE) and guanidine lysis buffer (GLB) methods; the efficiency and quality of these two methods were compared. The sequences of a mitochondrial gene (cytochrome c oxidase subunit I, COI) and a nuclear gene (28S rRNA) of C. gigas were analyzed to verify the origin of the extracted shell DNA. Finally, the DNA contents of the ventral edge, middle part, and dorsal edge of C. gigas shells were compared. The results showed that OSE had a higher DNA extraction efficiency than GLB; the oyster shell DNA was homologous to the oyster genome; the DNA content was higher in the ventral edge than in the middle part or in the dorsal edge of the C. gigas shell. This study not only reports an improved extraction method for the mollusk shell DNA, but also revealed that the DNA in the oyster shell originates from the oyster body and that the DNA content in different parts of the C. gigas shell showed obvious variance. These results provide supporting evidence for the hypothesis that oyster cells participate in shell formation, and also afford a nondestructive method for oyster genetic identification, which can promote the application of molecular biology technology in oyster breeding. In addition, a shell growth pattern of ‘Under Old & Exceeding Old’ was also proposed

The transmembrane channel-like 6 (TMC6) in primary sensory neurons involving thermal sensation via modulating M channels

Introduction: The transmembrane channel-like (TMC) protein family contains eight members, TMC1–TMC8. Among these members, only TMC1 and TMC2 have been intensively studied. They are expressed in cochlear hair cells and are crucial for auditory sensations. TMC6 and TMC8 contribute to epidermodysplasia verruciformis, and predispose individuals to human papilloma virus. However, the impact of TMC on peripheral sensation pain has not been previously investigated.Methods: RNAscope was employed to detect the distribution of TMC6 mRNA in DRG neurons. Electrophysiological recordings were conducted to investigate the effects of TMC6 on neuronal characteristics and M channel activity. Zn2+ indicators were utilized to detect the zinc concentration in DRG tissues and dissociated neurons. A series of behavioural tests were performed to assess thermal and mechanical sensation in mice under both physiological and pathological conditions.Results and Discussion: We demonstrated that TMC6 is mainly expressed in small and medium dorsal root ganglion (DRG) neurons and is involved in peripheral heat nociception. Deletion of TMC6 in DRG neurons hyperpolarizes the resting membrane potential and inhibits neuronal excitability. Additionally, the function of the M channel is enhanced in TMC6 deletion DRG neurons owing to the increased quantity of free zinc in neurons. Indeed, heat and mechanical hyperalgesia in chronic pain are alleviated in TMC6 knockout mice, particularly in the case of heat hyperalgesia. This suggests that TMC6 in the small and medium DRG neurons may be a potential target for chronic pain treatment