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As an alternative to in vivo Draize rabbit eye irritation test, this study aimed to construct an in silico model to predict the complete United Nations (UN) Globally Harmonized System (GHS) for cla...

Internet gaming disorder (IGD) has become an important social and psychiatric issue in recent years. To prevent IGD and provide the appropriate intervention, an accurate prediction method for identifying IGD is necessary. In this study, we investigated machine learning methods of multimodal neuroimaging data including Positron Emission Tomography (PET), Electroencephalography (EEG), and clinical features to enhance prediction accuracy. Unlike the conventional methods which usually concatenate all features into one feature vector, we adopted a multiple-kernel support vector machine (MK-SVM) to classify IGD. We compared the prediction performance of standard machine learning methods such as SVM, random forest, and boosting with the proposed method in patients with IGD (N = 28) and healthy controls (N = 24). We showed that the prediction accuracy of the optimal MK-SVM using three kinds of modalities was much higher than other conventional machine learning methods, with the highest accuracy being 86.5%, the sensitivity 89.3%, and the specificity 83.3%. Furthermore, we deduced that clinical variables had the highest contribution to the optimal IGD prediction model and that the other two modalities were also indispensable. We found that more efficient integration of multimodal data through kernel combination could contribute to better performance of the prediction model. This study is a novel attempt to integrate each method from different sources and suggests that integrating each method, such as self-administrated reports, PET, and EEG, improves the prediction of IGD.

We aimed to develop a machine learning (ML) classifier to detect and compare major psychiatric disorders using electroencephalography (EEG). We retrospectively collected data from medical records, intelligence quotient (IQ) scores from psychological assessments, and quantitative EEG (QEEG) at resting-state assessments from 945 subjects [850 patients with major psychiatric disorders (six large-categorical and nine specific disorders) and 95 healthy controls (HCs)]. A combination of QEEG parameters including power spectrum density (PSD) and functional connectivity (FC) at frequency bands was used to establish models for the binary classification between patients with each disorder and HCs. The support vector machine, random forest, and elastic net ML methods were applied, and prediction performances were compared. The elastic net model with IQ adjustment showed the highest accuracy. The best feature combinations and classification accuracies for discrimination between patients and HCs with adjusted IQ were as follows: schizophrenia = alpha PSD, 93.83%; trauma and stress-related disorders = beta FC, 91.21%; anxiety disorders = whole band PSD, 91.03%; mood disorders = theta FC, 89.26%; addictive disorders = theta PSD, 85.66%; and obsessive–compulsive disorder = gamma FC, 74.52%. Our findings suggest that ML in EEG may predict major psychiatric disorders and provide an objective index of psychiatric disorders.

Adolescent Internet addiction is an important social issue entailing extensive use of Internet and smartphones and its side effects. This study identified relevant psychological factors that affect excessive Internet use (EIU) and excessive smartphone use (ESU) in adolescents using structural equation modeling (SEM). A sample of 714 individuals drawn from lists of middle school students in South Korea completed self-administered questionnaires, including Young's Internet Addiction Test (Y-IAT), the Smartphone Addiction Scale (SAS), and various clinical and psychological scales measuring depression, anxiety, attention deficit/hyperactivity disorder (ADHD), aggression, expression of anger, and the behavioral inhibition system (BIS)/activation system (BAS). The final model, fitted using SEM, showed that both clinical characteristics, including ADHD symptoms, aggression, expression of anger, depression, and anxiety, and personality characteristics, represented by BIS/BAS, played important roles in the severity of EIU or ESU. In particular, affective components such as depression and anxiety were significantly associated with both EIU and ESU, whereas aggression, the expression of anger, and ADHD symptoms affected only EIU. Furthermore, the association between ESU and EIU was significant. Although personality characteristics measured by the BIS and BAS scores did not have direct effects on addiction, they were associated with clinical features and might be risk factors for addiction. The model revealed significant pathways from personality and clinical features to EIU and ESU in adolescents and informed our basic understanding of the meaningful predictors of these addictions and their direct and indirect influences.

In the essay ‘Postscript on the Societies of Control’, Deleuze discusses the differences between nineteenth-century capitalism and contemporary capitalism, characterising the former as the spaces of enclosure and the latter as the open circuits of the bank. In contemporary capitalism, ‘[m]an is no longer man enclosed, but man in debt’ ( Deleuze 1992 : 6). Deleuze claims that under financial capitalism, where the primary use of money is self-generation, economic relations are thought in terms of an asymmetrical power relationship between debtor and creditor, rather than an exchange between commodities. Taking up Deleuze's claim, this paper analyses how time functions in the formation of subjectivity under financial capitalism, by focusing on the temporal structure of debt. The indebted are expected to bind themselves to the past, not only in the moment they make a promise to pay back, but from that moment onwards; in this process, a subject finds himself passively subjected to the temporality determined by the condition of indebtedness, and yet he also actively reproduces and imposes the fact of indebtedness on himself by the feeling of guilt. Guilt, arising from the irreversibility of what has been done and resulting in the inability to proceed into the future, is central both to the indebted and the melancholic. Thus a melancholic subject emerges: a subject conditioned by the dominance of the past and the impossibility of the future.

Among the members of the fibroblast growth factor (FGF) family that affect the growth, differentiation, migration, and survival of many cell types, FGF2 is the most abundant in the central nervous system. Because of its wound healing effects, FGF2 has potential as a therapeutic agent. The protein is also added to the culture media to maintain stem cells. Expression and purification procedures for FGF2 that are highly efficient and low cost have been intensively investigated for the past two decades. Our current study focuses on the purification of FGF2 fused with b'a' domains of human protein disulfide isomerase to elevate overexpression, solubility, and stability with a simplified experimental procedure using only ion exchange chromatography, as well as on the confirmation of the biological activity of FGF2 on fibroblast Balb/c 3T3 cells and hippocampal neural cells.

Human interferon alpha-2b (IFNα-2b) has therapeutic applications as an antiviral and antiproliferative drug and has been used for a wide range of indications. Efficient production of IFNα-2b in Escherichia coli has been difficult because the protein tends to form inclusion bodies. This obstacle has garnered interest in efficiently expressing IFNα-2b and overcoming its poor solubility. In this study, seven N-terminal fusion partners - hexahistidine (His6), thioredoxin, glutathione S-transferase (GST), maltose-binding protein (MBP), N-utilization substance protein A, protein disulfide bond isomerase (PDI), and b'a' domain of PDI - were tested for soluble overexpression of codon-optimized IFNα-2b in E. coli. Low temperature increased the expression level of all of the tagged proteins except for the GST fusion. All the tags, except for His6 and GST, improved solubility. We purified IFNα-2b from the MBP-tagged fusion using immobilized metal affinity chromatography and anion exchange chromatography, and obtained a final yield of 7.2 mg from an initial 500-ml culture. The endotoxin level was 0.46 EU/µg. Biological activity was demonstrated using a luciferase assay, which showed a dose-dependent response with a calculated EC50 of 10.3 ± 5.9 pM. Our results demonstrate that using an MBP-tagged fusion is an efficient way to produce pure IFNα-2b.

Crotamine is a peptide toxin found in the venom of the rattlesnake Crotalus durissus terrificus. Inter- estingly, crotamine demonstrates promising anticancer, antimicrobial, and antifungal activities. The crotamine peptide can also deliver plasmids into rapidly dividing cells, such as cancer and stem cells, and demonstrates potent analgesic effects. Efficiently producing crotamine in mammalian cells is difficult because it is both cell-permeable and cytotoxic. Prokaryotic expression of this peptide is also difficult to maintain because it does not fold properly in the cytoplasm, resulting in aggregation and in the for- mation of inclusion bodies. In our current study, we show for the first time that N-terminal fusion with three protein tagsdN- utilization substance protein A (NusA), protein disulfide isomerase b 0a0 domain (PDIb0a0), and maltose- binding protein (MBP)denables the soluble overexpression of crotamine in the cytoplasm of Escher- ichia coli. MBP-tagged crotamine was purified using Ni affinity, anion exchange, and MBP chromatog- raphy. The tag was cleaved using TEV protease, and the final product was pure on a silver-stained gels. In total, 0.9 mg pure crotamine was obtained from each liter of bacterial culture with endotoxin level approximately 0.15 EU/mg, which is low enough to use in biomedical applications. The identity and intramolecular disulfide bonds were confirmed using MALDI-TOF MS analysis. Purified crotamine inhibited the hKv1.3 channel (but not hKv1.5) in a dose-dependent manner with IC50 value of 67.2 ± 44.7 nM (n ¼ 10), indicating the correct protein folding. The crotamine product fused with MBP at its N-terminus also inhibited the hKv1.3 channel, suggesting that the N-terminus is not involved in the channel binding of the toxin.

Human chemokine (C–C motif) ligand 2 (hCCL2) is a small cytokine in the CC chemokine family that attracts monocytes, memory T lymphocytes, and natural killer cells to the site of tissue injury- or infection-induced inflammation. hCCL2 has been implicated in the pathogeneses of diseases characterized by monocytic infiltrates, including psoriasis, rheumatoid arthritis, atherosclerosis, multiple sclerosis, and insulin-resistant diabetes. The prokaryotic overexpression of hCCL2 has been investigated previously in an attempt to develop biomedical applications for this factor, but this has been hampered by protein misfolding and aggregation into inclusion bodies. In our present study, we screened 7 protein tags—Trx, GST, MBP, NusA, His8, PDI, and PDIb′a′—for their ability to allow the soluble overexpression of hCCL2. Three tags—MBP, His8, and PDI—solubilized more than half of the expressed hCCL2 fusion proteins. Lowering the expression temperature to 18 °C significantly further improved the solubility of all fusion proteins. MBP was chosen for further study based on its solubility, expression level, ease of purification, and tag size. MBP-CCL2 was purified using conventional chromatography and cleaved using TEV or Factor Xa proteases. Biological activity was assessed using luciferase and cell migration assays. Factor Xa-cleaved hCCL2 was found to be active and TEV-cleaved hCCL2 showed relatively less activity. This is probably because the additional glycine residues present at the N-terminus of hCCL2 following TEV digestion interfere with the binding of hCCL2 to its receptor.

The temperature increase due to Joule heating in a nanopillar of a magnetic tunnel junction sandwiched by top and bottom electrodes was calculated by the finite element method. The results for the critical condition for the current-induced magnetization switching measured over a wide current-pulse range were taken from the literature. At long pulse widths, the temperature increase was solely dependent on the magnitude of the critical current density. However, no saturation in the temperature increase occurred for short pulse widths. In this case, the temperature increase additionally depended on the pulse width, so that a broad maximum occurred in the pulse width (or the critical current density) dependence of the temperature increase. The original results for the critical condition were corrected by accounting for the temperature increase and these corrected results, together with the Slonczewski equation, were used to extract an accurate value for the thermal stability factor.

The strong perpendicular magnetic anisotropy (PMA), indicated by a large coercivity of 590 Oe, is obtained in CoFeB/Pd multilayers through a systematic study that involves using various substrates (Si, glass, sapphire, and MgO) and seed layers (Al and Ta) and also varying the thickness of the seed layer. The PMA is nearly independent of the substrate when Al is used as a seed layer, but the dependence increases significantly with increasing seed layer thickness. The behavior becomes rather complicated for the multilayers with a Ta seed layer, showing a large substrate dependence and a large seed layer thickness dependence.