Assessment of the Purity of IMM-H014 and Its Related Substances for the Treatment of Metabolic-Associated Fatty Liver Disease Using Quantitative Nuclear Magnetic Resonance Spectroscopy.

An accurate, rapid, and selective quantitative nuclear magnetic resonance method was developed and validated to assess the purity of IMM-H014, a novel drug for the treatment of metabolic-associated fatty liver disease (MAFLD), and four related substances (impurities I, II, III, and IV). In this study, we obtained spectra of IMM--H014 and related substances in deuterated chloroform using dimethyl terephthalate (DMT) as the internal standard reference. Quantification was performed using the 1H resonance signals at δ 8.13 ppm for DMT and δ 6.5-7.5 ppm for IMM-H014 and its related substances. Several key experimental parameters were investigated and optimized, such as pulse angle and relaxation delay. Methodology validation was conducted based on the International Council for Harmonization guidelines and verified with satisfactory specificity, precision, linearity, accuracy, robustness, and stability. In addition, the calibration results of the samples were consistent with those obtained from the mass balance method. Thus, this research provides a reliable and practical protocol for purity analysis of IMM-H014 and its critical impurities and contributes to subsequent clinical quality control research.

The mutuality of social emotions: How the victim's reactive attitude influences the transgressor's emotional responses.

Would a transgressor be guiltier or less after receiving the victim's forgiving or blaming attitude? Everyday intuitions and empirical evidence are mixed in this regard, leaving how interpersonal attitudes shape the transgressor's reactive social emotions an open question. We combined a social interactive game with multivariate pattern analysis of fMRI data to address this question. Participants played an interactive game in an fMRI scanner where their incorrect responses could cause either high or low pain stimulation to an anonymous co-player. Following incorrect responses, participants were presented with the co-player's (i.e., the victim's) attitude towards the harm (Blame, Forgive, or Neutral). Behaviorally, the victim's attitude and the severity of harm interactively modulated the transgressor's social emotions, with expectation violation serving as a mediator. While unexpected forgiveness following severe harm amplified the participants' guilt, unexpected blame following minor harm reduced the participants' guilt and increased their anger. This role of expectation violation was supported by multivariate pattern analysis of fMRI, revealing a shared neural representation in ventral striatum in the processing of victim's attitude-induced guilt and anger. Moreover, we identified a neural re-appraisal process of guilt in the transgressor, with the involvement of area related to self-conscious processing (i.e., perigenual anterior cingulate cortex) before knowing the victim's attitude transiting to the involvement of other-regarding related area (i.e., temporoparietal junction) after knowing the victim's attitude. These findings uncover the neurocognitive bases underlying the transgressor's social emotional responses, and highlight the importance of the mutuality of social emotions.

Three-dimensional metal-semiconductor-metal AlN deep-ultraviolet detector.

Conventional metal-semiconductor-metal (MSM) ultraviolet (UV) detectors have the disadvantage of limited adjustable structural parameters, finite electrical field, and long carrier path. In this Letter, we demonstrate a three-dimensional (3D) MSM structural AlN-based deep-UV (DUV) detector, fabricated through simple trench etching and metal deposition, while flip bonding to the silicon substrate forms a flip-chip 3D-MSM (FC-3DMSM) device. 3D-MSM devices exhibit improved responsiveness and response speed, compared with conventional MSM devices. Time-dependent photoresponse of all devices is also investigated here. The enhanced performance of the 3D-MSM device is to be attributed to the intensified electrical field from the 3D metal electrode configuration and the inhibition of the carrier vertical transport, which unambiguously increases the carrier collection efficiency and migration speed, and thus the responsivity and speed as well. This work should advance the design and fabrication of AlN-based DUV detectors.

Internet addiction disorder detection of Chinese college students using several personality questionnaire data and support vector machine.

With the unprecedented development of the Internet, it also brings the challenge of Internet Addiction (IA), which is hard to diagnose and cure according to the state-of-art research. In this study, we explored the feasibility of machine learning methods to detect IA. We acquired a dataset consisting of 2397 Chinese college students from the University (Age: 19.17 ±â€¯0.70, Male: 64.17%) who completed Brief Self Control Scale (BSCS), the 11th version of Barratt Impulsiveness Scale (BIS-11), Chinese Big Five Personality Inventory (CBF-PI) and Chen Internet Addiction Scale (CIAS), where CBF-PI includes five sub-features (Openness, Extraversion, Conscientiousness, Agreeableness, and Neuroticism) and BSCS includes three sub-features (Attention, Motor and Non-planning). We applied Student's t-test on the dataset for feature selection and Support Vector Machines (SVMs) including C-SVM and ν-SVM with grid search for the classification and parameters optimization. This work illustrates that SVM is a reliable method for the assessment of IA and questionnaire data analysis. The best detection performance of IA is 96.32% which was obtained by C-SVM in the 6-feature dataset without normalization. Finally, the BIS-11, BSCS, Motor, Neuroticism, Non-planning, and Conscientiousness are shown to be promising features for the detection of IA.

Computer-aided pancreas segmentation based on 3D GRE Dixon MRI: a feasibility study.

BACKGROUND: Pancreas segmentation is of great significance for pancreatic cancer radiotherapy positioning, pancreatic structure, and function evaluation. PURPOSE: To investigate the feasibility of computer-aided pancreas segmentation based on optimized three-dimensional (3D) Dixon magnetic resonance imaging (MRI). MATERIAL AND METHODS: Seventeen healthy volunteers (13 men, 4 women; mean age = 53.4 ± 13.2 years; age range = 28-76 years) underwent routine and optimized 3D gradient echo (GRE) Dixon MRI at 3.0 T. The computer-aided segmentation of the pancreas was executed by the Medical Imaging Interaction ToolKit (MITK) with the traditional segmentation algorithm pipeline (a threshold method and a morphological method) on the opposed-phase and water images of Dixon. The performances of our proposed computer segmentation method were evaluated by Dice coefficients and two-dimensional (2D)/3D visualization figures, which were compared for the opposed-phase and water images of routine and optimized Dixon sequences. RESULTS: The dice coefficients of the computer-aided pancreas segmentation were 0.633 ± 0.080 and 0.716 ± 0.033 for opposed-phase and water images of routine Dixon MRI, respectively, while they were 0.415 ± 0.143 and 0.779 ± 0.048 for the optimized Dixon MRI, respectively. The Dice index was significantly higher based on the water images of optimized Dixon than those in the other three groups (all P values < 0.001), including water images of routine Dixon MRI and both of the opposed-phase images of routine and optimized Dixon sequences. CONCLUSION: Computer-aided pancreas segmentation based on Dixon MRI is feasible. The water images of optimized Dixon obtained the best similarity with a good stability.

Effects of Different Cognitive Trainings on Amnestic Mild Cognitive Impairment in the Elderly: A One-Year Longitudinal Functional Magnetic Resonance Imaging (MRI) Study.

BACKGROUND Cognitive training has been focused on the interventions of amnestic mild cognitive impairment (aMCI) in recent years, with poor understanding. MATERIAL AND METHODS The study participants with aMCI were screened in a previous intervention trial. Functional magnetic resonance imaging (fMRI) was adopted to investigate effects of single-domain cognitive training (SDCT) and multi-domain cognitive training (MDCT) on aMCI and to explore potential mechanisms. RESULTS There were significant differences in the grey matter volume of the middle frontal gyrus, superior parietal lobule, inferior temporal gyrus, fusiform gyrus, and ventral V3 between the MDCT/SDCT group and the control group (P<0.05). Regional homogeneity (ReHo) increased significantly in the right and left inferior frontal gyrus as well as in the left and right precentral gyrus after intervention in the MDCT group and the SDCT group. ReHo increased significantly in the right and left lingual gyrus of the MDCT group and the control group. ReHo reduced significantly in the right middle temporal gyrus of the MDCT group but increased significantly in the left middle temporal gyrus in the SDCT group and the control group. The voxel of grey matter in the precuneus was positively related to the language scores on RBANS (Repeatable Battery for the Assessment of Neuropsychological Status), and amygdala, fusiform gyrus, and hippocampus also had a positive relationship with delayed memory scores in RBANS of the MDCT group. In the MDCT group, the attention and reasoning scores were also positively related to the ReHo of middle temporal gyrus. CONCLUSIONS Both MDCT and SDCT may improve the aMCI at brain functional and structural levels; however, the MDCT group exhibited higher ReHo values in middle temporal gyrus and superior occipital gyrus. Also, it was confirmed that MDCT leads to better results than SDCT, showing a significant correlation of cognitive functions such as attention, memory, reasoning, and visual-spatial ability.

COMT Val158Met polymorphism influences the susceptibility to framing in decision-making: OFC-amygdala functional connectivity as a mediator.

Individuals tend to avoid risk in a gain frame, in which options are presented in a positive way, but seek risk in a loss frame, in which the same options are presented negatively. Previous studies suggest that emotional responses play a critical role in this "framing effect." Given that the Met allele of COMT Val158Met polymorphism (rs4680) is associated with the negativity bias during emotional processing, this study investigated whether this polymorphism is associated with individual susceptibility to framing and which brain areas mediate this gene-behavior association. Participants were genotyped, scanned in resting state, and completed a monetary gambling task with options (sure vs risky) presented as potential gains or losses. The Met allele carriers showed a greater framing effect than the Val/Val homozygotes as the former gambled more than the latter in the loss frame. Moreover, the gene-behavior association was mediated by resting-state functional connectivity (RSFC) between orbitofrontal cortex (OFC) and bilateral amygdala. Met allele carriers showed decreased RSFC, thereby demonstrating higher susceptibility to framing than Val allele carriers. These findings demonstrate the involvement of COMT Val158Met polymorphism in the framing effect in decision-making and suggest RSFC between OFC and amygdala as a neural mediator underlying this gene-behavior association. Hum Brain Mapp 37:1880-1892, 2016. © 2016 Wiley Periodicals, Inc.

EEG Classification for Hybrid Brain-Computer Interface Using a Tensor Based Multiclass Multimodal Analysis Scheme.

Electroencephalogram- (EEG-) based brain-computer interface (BCI) systems usually utilize one type of changes in the dynamics of brain oscillations for control, such as event-related desynchronization/synchronization (ERD/ERS), steady state visual evoked potential (SSVEP), and P300 evoked potentials. There is a recent trend to detect more than one of these signals in one system to create a hybrid BCI. However, in this case, EEG data were always divided into groups and analyzed by the separate processing procedures. As a result, the interactive effects were ignored when different types of BCI tasks were executed simultaneously. In this work, we propose an improved tensor based multiclass multimodal scheme especially for hybrid BCI, in which EEG signals are denoted as multiway tensors, a nonredundant rank-one tensor decomposition model is proposed to obtain nonredundant tensor components, a weighted fisher criterion is designed to select multimodal discriminative patterns without ignoring the interactive effects, and support vector machine (SVM) is extended to multiclass classification. Experiment results suggest that the proposed scheme can not only identify the different changes in the dynamics of brain oscillations induced by different types of tasks but also capture the interactive effects of simultaneous tasks properly. Therefore, it has great potential use for hybrid BCI.

Social status modulates the neural response to unfairness.

In human society, which is organized by social hierarchies, resources are usually allocated unequally and based on social status. In this study, we analyze how being endowed with different social statuses in a math competition affects the perception of fairness during asset allocation in a subsequent Ultimatum Game (UG). Behavioral data showed that when participants were in high status, they were more likely to reject unfair UG offers than in low status. This effect of social status correlated with activity in the right anterior insula (rAI) and with the functional connectivity between the rAI and a region in the anterior middle cingulate cortex, indicating that these two brain regions are crucial for integrating contextual factors and social norms during fairness perception. Additionally, there was an interaction between social status and UG offer fairness in the amygdala and thalamus, implicating the role of these regions in the modulation of social status on fairness perception. These results demonstrate the effect of social status on fairness perception and the potential neural underpinnings for this effect.

Reward breaks through center-surround inhibition via anterior insula.

Focusing attention on a target creates a center-surround inhibition such that distractors located close to the target do not capture attention. Recent research showed that a distractor can break through this surround inhibition when associated with reward. However, the brain basis for this reward-based attention is unclear. In this fMRI study, we presented a distractor associated with high or low reward at different distances from the target. Behaviorally the low-reward distractor did not capture attention and thus did not cause interference, whereas the high-reward distractor captured attention only when located near the target. Neural activity in extrastriate cortex mirrored the behavioral pattern. A comparison between the high-reward and the low-reward distractors presented near the target (i.e., reward-based attention) and a comparison between the high-reward distractors located near and far from the target (i.e., spatial attention) revealed a common frontoparietal network, including inferior frontal gyrus and inferior parietal sulcus as well as the visual cortex. Reward-based attention specifically activated the anterior insula (AI). Dynamic causal modelling showed that reward modulated the connectivity from AI to the frontoparietal network but not the connectivity from the frontoparietal network to the visual cortex. Across participants, the reward-based attentional effect could be predicted both by the activity in AI and by the changes of spontaneous functional connectivity between AI and ventral striatum before and after reward association. These results suggest that AI encodes reward-based salience and projects it to the stimulus-driven attentional network, which enables the reward-associated distractor to break through the surround inhibition in the visual cortex.

3-D ice shape measurements using mid-infrared laser scanning.

A general approach based on mid-infrared (MIR) laser scanning is proposed to measure the 3-D ice shape no matter whether the ice is composed of clear ice, rime ice, mixed ice, or even supercooled water droplets or films. This is possible because MIR radiation penetrates ice and water only within a depth of less than 10 micrometers. First, an MIR laser point scanning technique is implemented and verified on transparent glass and clear ice. Then, to improve efficiency, an MIR laser line scanning method is developed and validated on different models. At last, several sequential MIR laser line scans are applied to trace the 3-D shape evolution of the continuous ice accretion on an airfoil in an icing wind tunnel. The ice growth process can be well observed in the results. The MIR scan shows a good agreement with the traditional visible laser scan on a plastic replication of the final ice shape made by the mold and casting method.

Fast screening of dendrimer-binding compounds by diffusion NMR techniques.

High-throughput screening of dendrimer-binding drugs is essential for the design and optimization of dendrimer-based drug delivery systems. In this study, pulsed gradient spin echo (PGSE) NMR was used for fast screening dendrimer-binding compounds using common amino acids as a screening pool. Diffusion coefficients of the amino acids before and after the addition of poly(propylene imine) (PPI) dendrimer were used to rank the binding affinities of the amino acids to the dendrimer. Among the common amino acids, cysteine, glutamic acid, aspartic acid, and tryptophan show strong binding affinity to PPI dendrimer. Tryptophan forms inclusion complexes with PPI dendrimer through hydrophobic interactions, while other amino acids mainly bind with PPI dendrimer via ionic and hydrogen-bond interactions. The PGSE NMR-based screening method provides new insights into high-throughput screening of dendrimer-binding compounds and should facilitate the study of dendrimer-based host-guest systems.

Understanding the binding interactions between dendrimer and 18 common amino acids by NMR techniques.

In the present study, we focus on the interactions between poly(propylene imine) (PPI) dendrimer and 18 of the 20 common amino acids by several NMR techniques, including NMR titrations and NOESY analysis. Surface ionic interactions and interior encapsulations were observed, and the binding behavior of amino acids with PPI dendrimer depends much on the side-chain properties of the amino acid, such as charge and hydrophobic/hydrophilic properties. The (1)H NMR titration results show that the formation of PPI dendrimer-amino acid complexes are driven mainly by ionic interactions for all the amino acids except tryptophan, which is involved in strong hydrophobic interactions with the interior pockets of PPI. The hydrophobic encapsulation of tryptophan in PPI pockets is confirmed by NOESY analysis. Amino acids with negatively charged residues much more easily saturate the surface charges on PPI than amino acids with uncharged residues, whereas amino acids with positively charged residues are the most difficult to bind with the surface amine groups on the PPI dendrimer. A simultaneous occurrence of interior encapsulation (hydrophobic, hydrogen bond, or ionic interactions) and surface binding (ionic interactions) was observed for tryptophan, phenylalanine, arginine, lysine, histidine, cysteine, and asparagine, and a preferential surface ionic binding on the PPI surface rather than encapsulations in the interior was obtained for the other amino acids.