This study analyzes funding acknowledgments in scientific papers to investigate relationships between research sponsorship and publication impacts. We identify acknowledgments to research sponsors for nanotechnology papers published in the Web of Science during a one-year sample period. We examine the citations accrued by these papers and the journal impact factors of their publication titles. The results show that publications from grant sponsored research exhibit higher impacts in terms of both journal ranking and citation counts than research that is not grant sponsored. We discuss the method and models used, and the insights provided by this approach as well as it limitations.

The neural processing loop of language is complex but highly associated with Broca's and Wernicke's areas. The left dominance of these two areas was the earliest observation of brain asymmetry. It was demonstrated that the language network and its functional asymmetry during resting state were reproducible across institutions. However, the temporal reliability of resting-state language network and its functional asymmetry are still short of knowledge. In this study, we established a seed-based resting-state functional connectivity analysis of language network with seed regions located at Broca's and Wernicke's areas, and investigated temporal reliability of language network and its functional asymmetry. The language network was found to be temporally reliable in both short- and long-term. In the aspect of functional asymmetry, the Broca's area was found to be left lateralized, while the Wernicke's area is mainly right lateralized. Functional asymmetry of these two areas revealed high short- and long-term reliability as well. In addition, the impact of global signal regression (GSR) on reliability of the resting-state language network was investigated, and our results demonstrated that GSR had negligible effect on the temporal reliability of the resting-state language network. Our study provided methodology basis for future cross-culture and clinical researches of resting-state language network and suggested priority of adopting seed-based functional connectivity for its high reliability.

Although mesial temporal lobe epilepsy (mTLE) is characterized by the pathological changes in mesial temporal lobe, function alteration was also found in extratemporal regions. Our aim is to investigate the information flow between the epileptogenic zone (EZ) and other brain regions. Resting-state functional magnetic resonance imaging (RS-fMRI) data were recorded from 23 patients with left mTLE and matched controls. We first identified the potential EZ using the amplitude of low-frequency fluctuation (ALFF) of RS-fMRI signal, then performed voxel-wise Granger causality analysis between EZ and the whole brain. Relative to controls, patients demonstrated decreased driving effect from EZ to thalamus and basal ganglia, and increased feedback. Additionally, we found an altered causal relation between EZ and cortical networks (default mode network, limbic system, visual network and executive control network). The influence from EZ to right precuneus and brainstem negatively correlated with disease duration, whereas that from the right hippocampus, fusiform cortex, and lentiform nucleus to EZ showed positive correlation. These findings demonstrate widespread brain regions showing abnormal functional interaction with EZ. In addition, increased ALFF in EZ was positively correlated with the increased driving effect on EZ in patients, but not in controls. This finding suggests that the initiation of epileptic activity depends not only on EZ itself, but also on the activity emerging in large-scale macroscopic brain networks. Overall, this study suggests that the causal topological organization is disrupted in mTLE, providing valuable information to understand the pathophysiology of this disorder.

MELK (maternal embryonic leucine zipper kinase), which is a member of the AMPK (AMP-activated protein kinase)-related kinase family, plays important roles in diverse cellular processes and has become a promising drug target for certain cancers. However, the regulatory mechanism of MELK remains elusive. Here, we report the crystal structure of a fragment of human MELK that contains the kinase domain and ubiquitin-associated (UBA) domain. The UBA domain tightly binds to the back of the kinase domain, which may contribute to the proper conformation and activity of the kinase domain. Interestingly, the activation segment in the kinase domain displays a unique conformation that contains an intramolecular disulfide bond. The structural and biochemical analyses unravel the molecular mechanisms for the autophosphorylation/activation of MELK and the dependence of its catalytic activity on reducing agents. Thus, our results may provide the basis for designing specific MELK inhibitors for cancer treatment.

Complete mitochondrial (mt) genome sequences with duplicate control regions (CRs) have been detected in various animal species. In Testudines, duplicate mtCRs have been reported in the mtDNA of the Asian big-headed turtle, Platysternon megacephalum, which has three living subspecies. However, the evolutionary pattern of these CRs remains unclear. In this study, we report the completed sequences of duplicate CRs from 20 individuals belonging to three subspecies of this turtle and discuss the micro-evolutionary analysis of the evolution of duplicate CRs. Genetic distances calculated with MEGA 4.1 using the complete duplicate CR sequences revealed that within turtle subspecies, genetic distances between orthologous copies from different individuals were 0.63% for CR1 and 1.2% for CR2app:addword:respectively, and the average distance between paralogous copies of CR1 and CR2 was 4.8%. Phylogenetic relationships were reconstructed from the CR sequences, excluding the variable number of tandem repeats (VNTRs) at the 3' end using three methods: neighbor-joining, maximum likelihood algorithm, and Bayesian inference. These data show that any two CRs within individuals were more genetically distant from orthologous genes in different individuals within the same subspecies. This suggests independent evolution of the two mtCRs within each P. megacephalum subspecies. Reconstruction of separate phylogenetic trees using different CR components (TAS, CD, CSB, and VNTRs) suggested the role of recombination in the evolution of duplicate CRs. Consequently, recombination events were detected using RDP software with break points at ≈290 bp and ≈1,080 bp. Based on these results, we hypothesize that duplicate CRs in P. megacephalum originated from heterological ancestral recombination of mtDNA. Subsequent recombination could have resulted in homogenization during independent evolutionary events, thus maintaining the functions of duplicate CRs in the mtDNA of P. megacephalum.

Fibroblast growth factor receptors (FGFRs) are frequently altered in a variety of human cancer cells and are overexpressed in hepatocellular carcinoma (HCC). Several literatures have proven that they are efficacious for HCC therapy, however, the underlying mechanism remains unclear. Here, we found FGFR4 was overexpressed in HCC cell lines HepG2 and Hep3B and we used PD173074, an FGFR4 inhibitor, to explore the role of FGFR4 and its underlying mechanism in these cell lines. The results showed that PD173074 significantly arrested HepG2 and Hep3B cells in G1 phase and inhibited cell proliferation. Furthermore, Western blot analysis revealed that PD173074 decreased the levels of P-FRS2α, P-ERK, CDK2, cyclin E and NF-κB (p65) in the nucleus while it increased the levels of ubiquitin and CUL3, an E3 ubiquitin ligase which involves in cyclin E degradation. Meanwhile, the data from RT-qPCR showed that PD173074 also decreased miR-141 level. In conclusion, these results suggest that FGFR4 is involved in HCC by ERK/CUL3/cyclin E signaling pathway, and the finding may provide a potential theoretical basis for treatment by targeting FGFR4 in HCC.

The amplitude of low-frequency fluctuation (ALFF) measures resting-state functional magnetic resonance imaging (RS-fMRI) signal of each voxel. However, the unit of blood oxygenation level-dependent (BOLD) signal is arbitrary and hence ALFF is sensitive to the scale of raw signal. A well-accepted standardization procedure is to divide each voxel's ALFF by the global mean ALFF, named mALFF. Although fractional ALFF (fALFF), a ratio of the ALFF to the total amplitude within the full frequency band, offers possible solution of the standardization, it actually mixes with the fluctuation power within the full frequency band and thus cannot reveal the true amplitude characteristics of a given frequency band. The current study borrowed the percent signal change in task fMRI studies and proposed percent amplitude of fluctuation (PerAF) for RS-fMRI. We firstly applied PerAF and mPerAF (i.e., divided by global mean PerAF) to eyes open (EO) vs. eyes closed (EC) RS-fMRI data. PerAF and mPerAF yielded prominently difference between EO and EC, being well consistent with previous studies. We secondly performed test-retest reliability analysis and found that (PerAF ≈ mPerAF ≈ mALFF) > (fALFF ≈ mfALFF). Head motion regression (Friston-24) increased the reliability of PerAF, but decreased all other metrics (e.g. mPerAF, mALFF, fALFF, and mfALFF). The above results suggest that mPerAF is a valid, more reliable, more straightforward, and hence a promising metric for voxel-level RS-fMRI studies. Future study could use both PerAF and mPerAF metrics. For prompting future application of PerAF, we implemented PerAF in a new version of REST package named RESTplus.

Transcranial direct current stimulation (tDCS) can improve cognitive function. However, it is not clear how high-definition tDCS (HD-tDCS) regulates the cognitive function and its neural mechanism, especially in individuals with mild cognitive impairment (MCI). This study aimed to examine whether HD-tDCS can modulate cognitive function in individuals with MCI and to determine whether the potential variety is related to spontaneous brain activity changes recorded by resting-state functional magnetic resonance imaging (rs-fMRI). Forty-three individuals with MCI were randomly assigned to receive either 10 HD-tDCS sessions or 10 sham sessions to the left dorsolateral prefrontal cortex (L-DLPFC). The fractional amplitude of low-frequency fluctuation (fALFF) and the regional homogeneity (ReHo) was computed using rs-fMRI data from all participants. The results showed that the fALFF and ReHo values changed in multiple areas following HD-tDCS. Brain regions with significant decreases in fALFF values include the Insula R, Precuneus R, Thalamus L, and Parietal Sup R, while the Temporal Inf R, Fusiform L, Occipital Sup L, Calcarine R, and Angular R showed significantly increased in their fALFF values. The brain regions with significant increases in ReHo values include the Temporal Inf R, Putamen L, Frontal Mid L, Precentral R, Frontal Sup Medial L, Frontal Sup R, and Precentral L. We found that HD-tDCS can alter the intensity and synchrony of brain activity, and our results indicate that fALFF and ReHo analysis are sensitive indicators for the detection of HD-tDCS during spontaneous brain activity. Interestingly, HD-tDCS increases the ReHo values of multiple brain regions, which may be related to the underlying mechanism of its clinical effects, these may also be related to a potential compensation mechanism involving the mobilization of more regions to complete a function following a functional decline.

Natural resources are scarce in the Loess Plateau, and the ecological environment is fragile. Sustainable development requires special attention to resource and environmental carrying capacity (RECC). This study selected 24 representative cities in five natural areas of the Loess Plateau; used the entropy-weight-based TOPSIS method to evaluate and analyze the RECC of each city and region from 2013 to 2018; established a diagnosis model to identify the obstacle factors restricting the improvement of RECC; and constructed the theoretical framework of the RECC system mechanism. The results show that the RECC of the Loess Plateau is increasing in general but is relatively small. The environmental and social subsystems have the highest and lowest carrying capacities, respectively. There is an evident contradiction between economic development and the environment. Population density, investment in technological innovation, per capita sown area, and per capita water resources are the main obstacles affecting the improvement of RECC in the Loess Plateau. Such evaluations and diagnoses can support ecological civilization and sustainable development.

Effective and accurate diagnosis of attention-deficit/hyperactivity disorder (ADHD) is currently of significant interest. ADHD has been associated with multiple cortical features from structural MRI data. However, most existing learning algorithms for ADHD identification contain obvious defects, such as time-consuming training, parameters selection, etc. The aims of this study were as follows: (1) Propose an ADHD classification model using the extreme learning machine (ELM) algorithm for automatic, efficient and objective clinical ADHD diagnosis. (2) Assess the computational efficiency and the effect of sample size on both ELM and support vector machine (SVM) methods and analyze which brain segments are involved in ADHD.

Red blood cells (RBCs) are among the most intensively studied cells in natural history, elucidating numerous principles and ground-breaking knowledge in cell biology. Morphologically, RBCs are largely homogeneous, and most of the functional studies have been performed on large populations of cells, masking putative cellular variations. We studied human and mouse RBCs by live-cell video imaging, which allowed single cells to be followed over time. In particular we analysed functional responses to hormonal stimulation with lysophosphatidic acid (LPA), a signalling molecule occurring in blood plasma, with the Ca(2+) sensor Fluo-4. Additionally, we developed an approach for analysing the Ca(2+) responses of RBCs that allowed the quantitative characterization of single-cell signals. In RBCs, the LPA-induced Ca(2+) influx showed substantial diversity in both kinetics and amplitude. Also the age-classification was determined for each particular RBC and consecutively analysed. While reticulocytes lack a Ca(2+) response to LPA stimulation, old RBCs approaching clearance generated robust LPA-induced signals, which still displayed broad heterogeneity. Observing phospatidylserine exposure as an effector mechanism of intracellular Ca(2+) revealed an even increased heterogeneity of RBC responses. The functional diversity of RBCs needs to be taken into account in future studies, which will increasingly require single-cell analysis approaches. The identified heterogeneity in RBC responses is important for the basic understanding of RBC signalling and their contribution to numerous diseases, especially with respect to Ca(2+) influx and the associated pro-thrombotic activity.

The present study was designed to examine the effects of ginsenoside Rg1 on expression of peroxisome proliferator-activated receptor γ (PPARγ) and insulin-degrading enzyme (IDE) in the hippocampus of rat model of Alzheimer's disease (AD) to determine how ginsenoside Rg1 (Rg1) decreases Aβ levels in AD.

Fibrinogen-like protein 2 (fgl2) is highly expressed in microvascular endothelial cells in diseases associated with microcirculatory disturbances and plays a crucial role in microthrombosis. Previous studies have demonstrated that the Ser89 residue is a critical site for mouse fgl2 prothrombinase activity. The aim of this study was to investigate the prothrombinase inhibitory ability of antibodies against an hfgl2-derived peptide. The peptide was termed NPG-12 because it is located at the N-terminus of membrane-bound hfgl2, contains 12 amino acid residues (corresponding to residues 76 to 87), and is rich in Glu. This peptide was selected as an antigenic determinant to produce antibodies in immunized rabbits using the DNAStar and HomoloGene software program. Abundant hfgl2 expression was induced in human umbilical vein endothelial cells through treatment with TNF-α. The generated anti-NPG-12 antibodies specifically recognize fgl2, as determined by ELISA, Western Blot and immunostaining. Moreover, one-stage clotting and thrombin generation tests provide evidence that the antibodies can reduce the hfgl2 prothrombinase activity without affecting the platelet-poor plasma prothrombin time (PT) or the activated partial thromboplastin time (APTT). In addition, the antibodies exerted undetectable influence on the proliferation or activation of bulk T cell populations. In conclusion, the selected peptide sequence NPG-12 may be a critical domain for hfgl2 prothrombinase activity, and the development of inhibitors against this sequence may be promising for research or management of hfgl2-associated microcirculatory disturbances.

Well-defined motifs often make it easy to investigate protein function and localization. In plants, peroxisomal proteins are guided to peroxisomes mainly by a conserved type 1 (PTS1) or type 2 (PTS2) targeting signal, and the PTS1 motif is commonly used for peroxisome targeting protein prediction. Currently computational prediction of peroxisome targeted PTS1-type proteins are mostly based on the 3 amino acids PTS1 motif and the adjacent sequence which is less than 14 amino acid residue in length. The potential contribution of the adjacent sequences beyond this short region has never been well investigated in plants. In this work, we develop a bi-profile Bayesian SVM method to extract and learn position-based amino acid features for both PTS1 motifs and their extended adjacent sequences in plants. Our proposed model outperformed other implementations with similar applications and achieved the highest accuracy of 93.6% and 92.6% for Arabidosis and other plant species respectively. A large scale analysis for Arabidopsis, Rice, Maize, Potato, Wheat, and Soybean proteome was conducted using the proposed model and a batch of candidate PTS1 proteins were predicted. The DNA segments corresponding to the C-terminal sequences of 9 selected candidates were cloned and transformed into Arabidopsis for experimental validation, and 5 of them demonstrated peroxisome targeting.

Obese individuals are at greater risk for death from influenza virus infection. Paralleling human evidence, obese mice are also more susceptible to influenza infection mortality. However, the underlying mechanisms driving greater influenza severity in the obese remain unclear. Metabolic profiling has been utilized in infectious disease models to enhance prognostic or diagnostic methods, and to gain insight into disease pathogenesis by providing a more global picture of dynamic infection responses. Herein, metabolic profiling was used to develop a deeper understanding of the complex processes contributing to impaired influenza protection in obese mice and to facilitate generation of new explanatory hypotheses. Diet-induced obese and lean mice were infected with influenza A/Puerto Rico/8/34. 1H nuclear magnetic resonance-based metabolic profiling of urine, feces, lung, liver, mesenteric white adipose tissue, bronchoalveolar lavage fluid and serum revealed distinct metabolic signatures in infected obese mice, including perturbations in nucleotide, vitamin, ketone body, amino acid, carbohydrate, choline and lipid metabolic pathways. Further, metabolic data was integrated with immune analyses to obtain a more comprehensive understanding of potential immune-metabolic interactions. Of interest, uncovered metabolic signatures in urine and feces allowed for discrimination of infection status in both lean and obese mice at an early influenza time point, which holds prognostic and diagnostic implications for this methodology. These results confirm that obesity causes distinct metabolic perturbations during influenza infection and provide a basis for generation of new hypotheses and use of this methodology in detection of putative biomarkers and metabolic patterns to predict influenza infection outcome.