Depression, anxiety-like behavior and memory impairment are associated with increased oxidative stress and inflammation in a rat model of social stress

In the present study, we have examined the behavioral and biochemical effect of induction of psychological stress using a modified version of the resident-intruder model for social stress (social defeat). At the end of the social defeat protocol, body weights, food and water intake were recorded, depression and anxiety-like behaviors as well as memory function was examined. Biochemical analysis including oxidative stress measurement, inflammatory markers and other molecular parameters, critical to behavioral effects were examined. We observed a significant decrease in the body weight in the socially defeated rats as compared to the controls. Furthermore, social defeat increased anxiety-like behavior and caused memory impairment in rats (P<0.05). Socially defeated rats made significantly more errors in long term memory tests (P<0.05) as compared to control rats. Furthermore, brain extracellular signal-regulated kinase-1/2 (ERK1/2), and an inflammatory marker, interleukin (IL)-6 were activated (P<0.05), while the protein levels of glyoxalase (GLO)-1, glutathione reductase (GSR)-1, calcium/calmodulin-dependent protein kinase type (CAMK)-IV, cAMP-response-element-binding protein (CREB) and brain-derived neurotrophic factor (BDNF) were significantly less (P<0.05) in the hippocampus, but not in the prefrontal cortex and amygdala of socially defeated rats, when compared to control rats. We suggest that social defeat stress alters ERK1/2, IL-6, GLO1, GSR1, CAMKIV, CREB, and BDNF levels in specific brain areas, leading to oxidative stress-induced anxiety-depression-like behaviors and as well as memory impairment in rats.

Soy isoflavones and prostate cancer: a review of molecular mechanisms

Soy isoflavones are dietary components for which an association has been demonstrated with reduced risk of prostate cancer (PCa) in Asian populations. However, the exact mechanism by which these isoflavones may prevent the development or progression of PCa is not completely understood. There are a growing number of animal and in vitro studies that have attempted to elucidate these mechanisms. The predominant and most biologically active isoflavones in soy products, genistein, daidzein, equol, and glycetin, inhibit prostate carcinogenesis in some animal models. Cell-based studies show that soy isoflavones regulate genes that control cell cycle and apoptosis. In this review, we discuss the literature relevant to the molecular events that may account for the benefit of soy isoflavones in PCa prevention or treatment. These reports show that although soy isoflavone-induced growth arrest and apoptosis of PCa cells are plausible mechanisms, other chemo protective mechanisms are also worthy of consideration. These possible mechanisms include antioxidant defense, DNA repair, inhibition of angiogenesis and metastasis, potentiation of radio- and chemotherapeutic agents, and antagonism of estrogen- and androgen-mediated signaling pathways. Moreover, other cells in the cancer milieu, such as the fibroblastic stromal cells, endothelial cells, and immune cells, may be targeted by soy isoflavones, which may contribute to soy-mediated prostate cancer prevention. In this review, these mechanisms are discussed along with considerations about the doses and the preclinical models that have been used.

Identification of proteomic signatures associated with lung cancer and COPD

Lung cancer (LC) and chronic obstructive pulmonary disease (COPD) commonly coexist in smokers, and the presence of COPD increases the risk of developing LC. The aim of this study was to identify distinct proteomic profiles able to discriminate these two pathological entities. Protein content was assessed in the bronchoalveolar lavage (BAL) of 60 patients classified in four groups: COPD, COPD and LC, LC without COPD, and control with neither COPD nor LC. Proteins were separated into spots by bidimensional polyacrylamide gel electrophoresis (2D-PAGE) and examined by matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF/TOF). A total of 40 proteins were differentially expressed in the LC and/or COPD groups as compared with the control group. Distinct protein profiles were identified and validated for each pathological entity (LC and COPD). The main networks involved were related to inflammatory signalling, free radical scavenging and oxidative stress response, and glycolysis and gluconeogenesis pathways. The most relevant signalling link between LC and COPD was through the NF-κB pathway. In conclusion, the protein profiles identified contribute to elucidate the underlying pathogenic pathways of both diseases, and provide new tools of potential use as biomarkers for the early diagnosis of LC.

BIOLOGICAL SIGNIFICANCE

Sequence coverage. The protein sequence coverage (95%) was estimated for specific proteins by the percentage of matching amino acids from the identified peptides having confidence greater than or equal to 95% divided by the total number of amino acids in the sequence. Ingenuity Pathways Analysis. Mapping of our proteins onto biological pathways and disease networks demonstrated that 22 proteins were linked to inflammatory signalling (p-value: 1.35 10(-08)-1.42 10(-02)), 15 proteins were associated with free radical scavenging and oxidative stress response (p-value: 4.93 10(-11)-1.27 10(-02)), and 9 proteins were related with glycolysis and gluconeogenesis pathways (p-value: 7.39 10(-09)-1.58 10(-02)).

Identifying and removing widespread signal deflections from fMRI data: Rethinking the global signal regression problem

One of the most controversial procedures in the analysis of resting-state functional magnetic resonance imaging (rsfMRI) data is global signal regression (GSR): the removal, via linear regression, of the mean signal averaged over the entire brain. On one hand, the global mean signal contains variance associated with respiratory, scanner-, and motion-related artifacts, and its removal via GSR improves various quality-control metrics, enhances the anatomical specificity of functional-connectivity patterns, and can increase the behavioral variance explained by such patterns. On the other hand, GSR alters the distribution of regional signal correlations in the brain, can induce artifactual anticorrelations, may remove real neural signal, and can distort case-control comparisons of functional-connectivity measures. Global signal fluctuations can be identified visually from a matrix of colour-coded signal intensities, called a carpet plot, in which rows represent voxels and columns represent time. Prior to GSR, large, periodic bands of coherent signal changes that affect most of the brain are often apparent; after GSR, these apparently global changes are greatly diminished. Here, using three independent datasets, we show that reordering carpet plots to emphasize cluster structure in the data reveals a greater diversity of spatially widespread signal deflections (WSDs) than previously thought. Their precise form varies across time and participants, and GSR is only effective in removing specific kinds of WSDs. We present an alternative, iterative correction method called Diffuse Cluster Estimation and Regression (DiCER), that identifies representative signals associated with large clusters of coherent voxels. DiCER is more effective than GSR at removing diverse WSDs as visualized in carpet plots, reduces correlations between functional connectivity and head-motion estimates, reduces inter-individual variability in global correlation structure, and results in comparable or improved identification of canonical functional-connectivity networks. Using task fMRI data across 47 contrasts from 7 tasks in the Human Connectome Project, we also present evidence that DiCER is more successful than GSR in preserving the spatial structure of expected task-related activation patterns. Our findings indicate that care must be exercised when examining WSDs (and their possible removal) in rsfMRI data, and that DiCER is a viable alternative to GSR for removing anatomically widespread and temporally coherent signals. All code for implementing DiCER and replicating our results is available at https://github.com/BMHLab/DiCER.

A stress sensor based on Galvanic Skin Response (GSR) controlled by ZigBee

Sometimes, one needs to control different emotional situations which can lead the person suffering them to dangerous situations, in both the medium and short term. There are studies which indicate that stress increases the risk of cardiac problems. In this study we have designed and built a stress sensor based on Galvanic Skin Response (GSR), and controlled by ZigBee. In order to check the device's performance, we have used 16 adults (eight women and eight men) who completed different tests requiring a certain degree of effort, such as mathematical operations or breathing deeply. On completion, we appreciated that GSR is able to detect the different states of each user with a success rate of 76.56%. In the future, we plan to create an algorithm which is able to differentiate between each state.

Electroencephalography Based Fusion Two-Dimensional (2D)-Convolution Neural Networks (CNN) Model for Emotion Recognition System

The purpose of this study is to improve human emotional classification accuracy using a convolution neural networks (CNN) model and to suggest an overall method to classify emotion based on multimodal data. We improved classification performance by combining electroencephalogram (EEG) and galvanic skin response (GSR) signals. GSR signals are preprocessed using by the zero-crossing rate. Sufficient EEG feature extraction can be obtained through CNN. Therefore, we propose a suitable CNN model for feature extraction by tuning hyper parameters in convolution filters. The EEG signal is preprocessed prior to convolution by a wavelet transform while considering time and frequency simultaneously. We use a database for emotion analysis using the physiological signals open dataset to verify the proposed process, achieving 73.4% accuracy, showing significant performance improvement over the current best practice models.

A head-to-head comparison of SCRalyze and Ledalab, two model-based methods for skin conductance analysis

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Comparison of two developed methods for model-based analysis of phasic skin conductance responses.

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Four datasets are used to compare predictive validity.

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SCRalyze shows higher predictive validity than Ledalab in 4 of 5 comparisons, and equal predictive validity in the fifth.

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SCRalyze shows higher predictive validity than peak-scoring in all comparisons.

Model-based analysis of skin conductance responses (SCR) can furnish less noisy estimates of sympathetic arousal (SA) than operational peak scoring approaches, as shown in previous work. Here, I compare two model-based methods for analysis of evoked (stimulus-locked) SCR, implemented in two software packages, SCRalyze and Ledalab, with respect to their sensitivity in recovering SA. Four datasets are analysed to compare predictive validity, i.e. the sensitivity to distinguish pairs of SA states that are known to be different. SCRalyze was significantly better able than Ledalab to recover this known difference in four out of five tested contrasts and comparable in the remaining one. SCRalyze performed significantly better than conventional analysis in all contrasts. I conclude that the model-based method engendered in SCRalyze is currently the best available approach to provide robust and sensitive estimates of sympathetic arousal.

Plastidial metabolite MEcPP induces a transcriptionally centered stress-response hub via the transcription factor CAMTA3

The general stress response (GSR) is an evolutionarily conserved rapid and transient transcriptional reprograming of genes central for transducing environmental signals into cellular responses, leading to metabolic and physiological readjustments to cope with prevailing conditions. Defining the regulatory components of the GSR will provide crucial insight into the design principles of early stress-response modules and their role in orchestrating master regulators of adaptive responses. Overaccumulation of methylerythritol cyclodiphosphate (MEcPP), a bifunctional chemical entity serving as both a precursor of isoprenoids produced by the plastidial methylerythritol phosphate (MEP) pathway and a stress-specific retrograde signal, in ceh1 (constitutively expressing hydroperoxide lyase1)-mutant plants leads to large-scale transcriptional alterations. Bioinformatic analyses of microarray data in ceh1 plants established the overrepresentation of a stress-responsive cis element and key GSR marker, the rapid stress response element (RSRE), in the promoters of robustly induced genes. ceh1 plants carrying an established 4×RSRE:Luciferase reporter for monitoring the GSR support constitutive activation of the response in this mutant background. Genetics and pharmacological approaches confirmed the specificity of MEcPP in RSRE induction via the transcription factor CALMODULIN-BINDING TRANSCRIPTION ACTIVATOR 3 (CAMTA3), in a calcium-dependent manner. Moreover, CAMTA3-dependent activation of IRE1a (inositol-requiring protein-1) and bZIP60 (basic leucine zipper 60), two RSRE containing unfolded protein-response genes, bridges MEcPP-mediated GSR induction to the potentiation of protein-folding homeostasis in the endoplasmic reticulum. These findings introduce the notion of transcriptional regulation by a key plastidial retrograde signaling metabolite that induces nuclear GSR, thereby offering a window into the role of interorgannellar communication in shaping cellular adaptive responses.

Sex differences in chemosensation: sensory or emotional?

Although the first sex-dependent differences in chemosensory processing were reported in the scientific literature over 60 years ago, the underlying mechanisms are still unknown. Generally, more pronounced sex-dependent differences are noted with increased task difficulty or with increased levels of intranasal irritation produced by the stimulus. Whether differences between the sexes arise from differences in chemosensory sensitivity of the two intranasal sensory systems involved or from differences in cognitive processing associated with emotional evaluation of the stimulants is still not known. We used simultaneous and complementary measures of electrophysiological (EEG), psychophysiological, and psychological responses to stimuli varying in intranasal irritation and odorousness to investigate whether sex differences in the processing of intranasal irritation are mediated by varying sensitivity of the involved sensory systems or by differences in cognitive and/or emotional evaluation of the irritants. Women perceived all stimulants more irritating and they exhibited larger amplitudes of the late positive deflection of the event-related potential than men. No significant differences in sensory sensitivity, anxiety, and arousal responses could be detected. Our findings suggest that men and women process intranasal irritation differently. Importantly, the differences cannot be explained by variation in sensory sensitivity to irritants, differences in anxiety, or differences in physiological arousal. We propose that women allocate more attention to potentially noxious stimuli than men do, which eventually causes differences in cognitive appraisal and subjective perception.

Glutathione synthesis is compromised in erythrocytes from individuals with HIV

We demonstrated that the levels of enzymes responsible for the synthesis of glutathione (GSH) such as glutathione synthase (GSS), glutamate-cysteine ligase-catalytic subunit (GCLC), and glutathione reductase (GSR) were significantly reduced in the red blood cells (RBCs) isolated from individuals with human immunodeficiency virus (HIV) infection and this reduction correlated with decreased levels of intracellular GSH. GSH content in RBCs can be used as a marker for increased overall oxidative stress and immune dysfunctions caused by HIV infection. Our data supports our hypothesis that compromised levels of GSH in HIV infected individuals’ is due to decreased levels of GSH-synthetic enzymes. The role of GSH in combating oxidative stress and improving the functions of immune cells in HIV patients’ indicates the benefit of an antioxidant supplement which can reduce the cellular damage and promote the functions of immune cells.

Dynamic causal modeling of spontaneous fluctuations in skin conductance

Spontaneous fluctuations (SF) in skin conductance are often used to index sympathetic arousal and emotional states. SF are caused by sudomotor nerve activity (SNA), which is a direct indicator of sympathetic arousal. Here, we describe a dynamic causal model (DCM) of how SNA causes SF, and apply variational Bayesian model inversion to infer SNA, given empirically observed SF. The estimated SNA bears a relationship to the number of SF as derived from conventional (semi-visual) analysis. Crucially, we show that, during public speaking induced anxiety, the estimated number of SNA bursts is a better predictor of the (known) psychological state than the number of SF. We suggest dynamic causal modeling of SF potentially allows a more precise and informed inference about arousal than purely descriptive methods.

GSH-dependent antioxidant defense contributes to the acclimation of colon cancer cells to acidic microenvironment

Due to increased glycolysis and poor local perfusion, solid tumors are usually immersed in an acidic microenvironment. While extracellular acidosis is cytotoxic, cancer cells eventually become acclimated to it. While previous studies have addressed the acute effect of acidosis on cancer cells, little is known about how cancer cells survive chronic acidosis. In this study we exposed colorectal cancer (CRC) cells (HCT15, HCT116 and LoVo) to acidic pH (pH 6.5) continuously for over three months and obtained CRC cells that become acclimated to acidic pH, designated as CRC-acidosis-acclimated or CRC-AA. We unexpectedly found that while acute exposure to low pH resulted in an increase in the level of intracellular reactive oxygen species (ROS), CRC-AA cells exhibited a significantly reduced level of ROS when compared to ancestor cells. CRC-AA cells were found to maintain a higher level of reduced glutathione, via the upregulation of CD44 and glutathione reductase (GSR), among others, than their ancestor cells. Importantly, CRC-AA cells were more sensitive to agents that deplete GSH. Moreover, downregulation of GSR by RNA interference was more deleterious to CRC-AA cells than to control cells. Together, our results demonstrate a critical role of glutathione-dependent antioxidant defense in acclimation of CRC cells to acidic extracellular pH.

Polymorphisms in oxidative stress-related genes and mortality in breast cancer patients--potential differential effects by radiotherapy?

We assessed whether variants in 22 oxidative stress-related genes are associated with mortality of breast cancer patients and whether the associations differ according to radiotherapy. Using a prospective cohort of 1348 postmenopausal breast cancer patients, we estimated hazard ratios (HR) and 95% confidence intervals (CI) for 109 single nucleotide polymorphisms (SNPs) using Cox proportional hazards regression. Validation of results was attempted using two Scandinavian studies. Eleven SNPs in MT2A, NFE2L2, NQO1, PRDX1, and PRDX6 were significantly associated with overall mortality after a median follow-up of 5.7 years. Three SNPs in NQO1 (rs2917667) and in PRDX6 (rs7314, rs4916362) were consistently associated with increased risk of dying across all three study populations (pooled: HRNQO1_rs2917667 1.20, 95% CI 1.00-1.44, p = 0.051; HRPRDX6_rs7314 1.16, 95% CI 1.00-1.35, p = 0.056, HRPRDX6_rs4916362 1.14 95% CI 1.00-1.32, p = 0.062). Potential effect modification by radiotherapy was found for CAT_rs769218. In conclusion, genetic variants in NQO1 and PRDX6 may modify breast cancer prognosis.

Identification of differentially-expressed genes potentially implicated in drought response in pitaya (Hylocereus undatus) by suppression subtractive hybridization and cDNA microarray analysis

Drought is one of the most severe threats to the growth, development and yield of plant. In order to unravel the molecular basis underlying the high tolerance of pitaya (Hylocereus undatus) to drought stress, suppression subtractive hybridization (SSH) and cDNA microarray approaches were firstly combined to identify the potential important or novel genes involved in the plant responses to drought stress. The forward (drought over drought-free) and reverse (drought-free over drought) suppression subtractive cDNA libraries were constructed using in vitro shoots of cultivar 'Zihonglong' exposed to drought stress and drought-free (control). A total of 2112 clones, among which half were from either forward or reverse SSH library, were randomly picked up to construct a pitaya cDNA microarray. Microarray analysis was carried out to verify the expression fluctuations of this set of clones upon drought treatment compared with the controls. A total of 309 expressed sequence tags (ESTs), 153 from forward library and 156 from reverse library, were obtained, and 138 unique ESTs were identified after sequencing by clustering and blast analyses, which included genes that had been previously reported as responsive to water stress as well as some functionally unknown genes. Thirty six genes were mapped to 47 KEGG pathways, including carbohydrate metabolism, lipid metabolism, energy metabolism, nucleotide metabolism, and amino acid metabolism of pitaya. Expression analysis of the selected ESTs by reverse transcriptase polymerase chain reaction (RT-PCR) corroborated the results of differential screening. Moreover, time-course expression patterns of these selected ESTs further confirmed that they were closely responsive to drought treatment. Among the differentially expressed genes (DEGs), many are related to stress tolerances including drought tolerance. Thereby, the mechanism of drought tolerance of this pitaya genotype is a very complex physiological and biochemical process, in which multiple metabolism pathways and many genes were implicated. The data gained herein provide an insight into the mechanism underlying the drought stress tolerance of pitaya, as well as may facilitate the screening of candidate genes for drought tolerance.

Portable System for Real-Time Detection of Stress Level

Currently, mental stress is a major problem in our society. It is related to a wide variety of diseases and is mainly caused by daily-life factors. The use of mobile technology for healthcare purposes has dramatically increased during the last few years. In particular, for out-of-lab stress detection, a considerable number of biosignal-based methods and systems have been proposed. However, these approaches have not matured yet into applications that are reliable and useful enough to significantly improve people’s quality of life. Further research is needed. In this paper, we propose a portable system for real-time detection of stress based on multiple biosignals such as electroencephalography, electrocardiography, electromyography, and galvanic skin response. In order to validate our system, we conducted a study using a previously published and well-established methodology. In our study, ten subjects were stressed and then relaxed while their biosignals were simultaneously recorded with the portable system. The results show that our system can classify three levels of stress (stress, relax, and neutral) with a resolution of a few seconds and 86% accuracy. This suggests that the proposed system could have a relevant impact on people’s lives. It can be used to prevent stress episodes in many situations of everyday life such as work, school, and home.

The Sample Size Matters: To What Extent the Participant Reduction Affects the Outcomes of a Neuroscientific Research. A Case-Study in Neuromarketing Field

The sample size is a crucial concern in scientific research and even more in behavioural neurosciences, where besides the best practice it is not always possible to reach large experimental samples. In this study we investigated how the outcomes of research change in response to sample size reduction. Three indices computed during a task involving the observations of four videos were considered in the analysis, two related to the brain electroencephalographic (EEG) activity and one to autonomic physiological measures, i.e., heart rate and skin conductance. The modifications of these indices were investigated considering five subgroups of sample size (32, 28, 24, 20, 16), each subgroup consisting of 630 different combinations made by bootstrapping n (n = sample size) out of 36 subjects, with respect to the total population (i.e., 36 subjects). The correlation analysis, the mean squared error (MSE), and the standard deviation (STD) of the indexes were studied at the participant reduction and three factors of influence were considered in the analysis: the type of index, the task, and its duration (time length). The findings showed a significant decrease of the correlation associated to the participant reduction as well as a significant increase of MSE and STD (p < 0.05). A threshold of subjects for which the outcomes remained significant and comparable was pointed out. The effects were to some extents sensitive to all the investigated variables, but the main effect was due to the task length. Therefore, the minimum threshold of subjects for which the outcomes were comparable increased at the reduction of the spot duration.

Identification and clinical validation of metastasis-associated biomarkers based on large-scale samples in colon-adenocarcinoma

AIM

Distant metastasis is the main cause of death in patients with colon-adenocarcinoma(COAD). Due to the lack of effective molecular markers and treatment, the prognosis of patients with metastatic colon cancer is still rather poor.

METHODS

Metastatic related signature (MRS) of stage I and stage IV in colon cancer were identified from different cohorts. Univariate cox regression is used to analyze the relationship between MRS and the overall survival. L1000FWD and DGIdb databases are used to identify molecular drugs. Expression and functional experimental validation of the hub MRS were carried out.

RESULTS

16 MRS were identified, of which 14 MRS was significantly correlated with overall survival. Further functional enrichment analysis showed that MRS was significantly involved with important biological functions such as cell migration, and apoptosis. As important metastatic related genes, GSR, FAS and CYP1B1 have significant interaction with drug molecules. Further studies have confirmed that the expression of FAS and GSR is low, and inhibition of its expression can promote the metastasis of COAD. CYP1B1 expression is highly expressed, and inhibition of its expression can attenuate the malignant biological behavior of colon cancer.

CONCLUSION

Our research could increase the understanding of the mechanism of colon cancer metastasis and provide theoretical basis for the treatment of metastatic colon cancer.

CNN and LSTM-Based Emotion Charting Using Physiological Signals

Novel trends in affective computing are based on reliable sources of physiological signals such as Electroencephalogram (EEG), Electrocardiogram (ECG), and Galvanic Skin Response (GSR). The use of these signals provides challenges of performance improvement within a broader set of emotion classes in a less constrained real-world environment. To overcome these challenges, we propose a computational framework of 2D Convolutional Neural Network (CNN) architecture for the arrangement of 14 channels of EEG, and a combination of Long Short-Term Memory (LSTM) and 1D-CNN architecture for ECG and GSR. Our approach is subject-independent and incorporates two publicly available datasets of DREAMER and AMIGOS with low-cost, wearable sensors to extract physiological signals suitable for real-world environments. The results outperform state-of-the-art approaches for classification into four classes, namely High Valence-High Arousal, High Valence-Low Arousal, Low Valence-High Arousal, and Low Valence-Low Arousal. Emotion elicitation average accuracy of 98.73% is achieved with ECG right-channel modality, 76.65% with EEG modality, and 63.67% with GSR modality for AMIGOS. The overall highest accuracy of 99.0% for the AMIGOS dataset and 90.8% for the DREAMER dataset is achieved with multi-modal fusion. A strong correlation between spectral- and hidden-layer feature analysis with classification performance suggests the efficacy of the proposed method for significant feature extraction and higher emotion elicitation performance to a broader context for less constrained environments.

Genomic and Phenotypic Analyses Reveal Mechanisms Underlying Homing Ability in Pigeon

The homing pigeon was selectively bred from the domestic pigeon for a homing ability over long distances, a very fascinating but complex behavioral trait. Here, we generate a total of 95 whole genomes from diverse pigeon breeds. Comparing the genomes from the homing pigeon population with those from other breeds identifies candidate positively selected genes, including many genes involved in the central nervous system, particularly spatial learning and memory such as LRP8. Expression profiling reveals many neuronal genes displaying differential expression in the hippocampus, which is the key organ for memory and navigation and exhibits significantly larger size in the homing pigeon. In addition, we uncover a candidate gene GSR (encoding glutathione-disulfide reductase) experiencing positive selection in the homing pigeon. Expression profiling finds that GSR is highly expressed in the wattle and visual pigment cell layer, and displays increased expression levels in the homing pigeon. In vitro, a magnetic field stimulates increases in calcium ion concentration in cells expressing pigeon GSR. These findings support the importance of the hippocampus (functioning in spatial memory and navigation) for homing ability, and the potential involvement of GSR in pigeon magnetoreception.

Analysis of gunshot residues as trace in nasal mucus by GFAAS

When a gun is fired, the majority of gunshot residues are deposited on the shooter's hands. But these residues disappear through contact with surfaces or washing. Therefore, the maximum time frame to find GSR on a suspect's hands is 8h. The mucus, inside of a nostril, forms a surface layer where they are trapped foreign particles. In this way, mucus inside of a gunshot suspect's nostrils could act like an adhesive medium to stick on it gaseous particles from a gunshot. In this study, the presence of GSR in nasal mucus and its residence time is examined. A new procedure for the sampling of possible gunshot residue accumulated in the nasal mucus is designed. Samples are taken with cotton swabs moistened with a solution of EDTA and, after an acid digestion, are analysed by graphite furnace atomic absorption spectrometry. In addition, samples of hands are taken for comparison purposes. GSR recovery has been successful. The concentration of GSR in nasal mucus is found to be lower than on the hands, but with a longer residence time. Thus, it is possible to expand the sampling time of a suspect also, as nasal mucus cannot be contaminated by handling weapons.

Gunshot residue contamination of the hands of police officers following start-of-shift handling of their firearm

If police officers are contaminated with gunshot residue (GSR) through the normal receiving, checking, loading, and securing of their issued firearm, there is the potential for secondary transfer of GSR to anyone those officers arrest during their shift. This 3-part study examined the level of GSR contamination of police officers following the start-of-shift handling of their standard issue firearm, the impact that hand-washing or the use of a self-drying hand-wash had on the level of GSR contamination, and the likelihood of officers re-contaminating their hands through contact with the exposed hand-grip of their holstered hand-gun. Almost 85% (28/33) of officers sampled had 3-component GSR particles on their hands immediately following the start-of-shift handling of their firearm. There was an average of 64 such particles over the 33 officers sampled. Of the 17 officers who washed their hands after securing their firearm, a single 3-component particle was recovered from the hands of one officer. GSR particles (maximum of 4) were recovered from 3 of the 14 officers who used self-drying hand gel following firearm handling. 3-component particles (maximum of 7) were recovered from the hand-grips of 12 of the 34 unissued handguns sampled.

How Neurophysiological Measures Can be Used to Enhance the Evaluation of Remote Tower Solutions

New solutions in operational environments are often, among objective measurements, evaluated by using subjective assessment and judgment from experts. Anyhow, it has been demonstrated that subjective measures suffer from poor resolution due to a high intra and inter-operator variability. Also, performance measures, if available, could provide just partial information, since an operator could achieve the same performance but experiencing a different workload. In this study, we aimed to demonstrate: (i) the higher resolution of neurophysiological measures in comparison to subjective ones; and (ii) how the simultaneous employment of neurophysiological measures and behavioral ones could allow a holistic assessment of operational tools. In this regard, we tested the effectiveness of an electroencephalography (EEG)-based neurophysiological index (W_EEG index) in comparing two different solutions (i.e., Normal and Augmented) in terms of experienced workload. In this regard, 16 professional air traffic controllers (ATCOs) have been asked to perform two operational scenarios. Galvanic Skin Response (GSR) has also been recorded to evaluate the level of arousal (i.e., operator involvement) during the two scenarios execution. NASA-TLX questionnaire has been used to evaluate the perceived workload, and an expert was asked to assess performance achieved by the ATCOs. Finally, reaction times on specific operational events relevant for the assessment of the two solutions, have also been collected. Results highlighted that the Augmented solution induced a local increase in subjects performance (Reaction times). At the same time, this solution induced an increase in the workload experienced by the participants (W_EEG). Anyhow, this increase is still acceptable, since it did not negatively impact the performance and has to be intended only as a consequence of the higher engagement of the ATCOs. This behavioral effect is totally in line with physiological results obtained in terms of arousal (GSR), that increased during the scenario with augmentation. Subjective measures (NASA-TLX) did not highlight any significant variation in perceived workload. These results suggest that neurophysiological measure provide additional information than behavioral and subjective ones, even at a level of few seconds, and its employment during the pre-operational activities (e.g., design process) could allow a more holistic and accurate evaluation of new solutions.

MicroRNA-362-5p promotes the proliferation and inhibits apoptosis of trophoblast cells via targeting glutathione-disulfide reductase

Gestational diabetes mellitus (GDM), a common complication of pregnancy, harms the health of pregnant women and fetuses. MicroRNAs (miRNAs) dysregulation in placenta is involved in GDM. Herein, we explored the roles of miR-362-5p in GDM. After high glucose (HG) treated HTR-8/SVneo cells, CCK-8 and flow cytometry were conducted to assess the capability of the proliferation and apoptosis, respectively. The data demonstrated that HG inhibited proliferation and induced apoptosis of HTR-8/SVneo cells. MiR-362-5p level was reduced in HG-treated cells and placenta tissues of GDM patients, measured by qPCR. Overexpressed miR-362-5p accelerated the proliferation and restrained apoptosis of HG-treated cells. Furthermore, glutathione-disulfide reductase (GSR) was verified as a target of miR-362-5p, through TargetScan database and dual-luciferase reporter assay. GSR was upregulated in GDM placenta tissues and was negatively regulated by miR-362-5p. Enforced GSR level abolished the effects of miR-362-5p overexpression on the proliferation and apoptosis of HTR-8/SVneo cells. Furthermore, miR-362-5p increased p-PI3K, p-AKT and bcl-2, while reduced bax and cleaved caspase3, which were abolished by GSR. In conclusion, miR-362-5p promoted cell proliferation and inhibited apoptosis via targeting GSR and activating PI3K/AKT pathway. The findings mentioned above suggested that miR-362-5p might be a therapy target of GDM.

Sympathetic nerve activity can be estimated from skin conductance responses - a comment on Henderson et al. (2012)

A recent paper by Henderson et al. (2012) claimed that skin sympathetic nerve activity (SSNA) can not be retrieved from skin conductance responses (SCR). Here, I argue that this claim is not supported by the literature, and comment on contemporary approaches of estimating SSNA from SCR using biophysical models.

An Exploration of Machine Learning Methods for Robust Boredom Classification Using EEG and GSR Data

In recent years, affective computing has been actively researched to provide a higher level of emotion-awareness. Numerous studies have been conducted to detect the user's emotions from physiological data. Among a myriad of target emotions, boredom, in particular, has been suggested to cause not only medical issues but also challenges in various facets of daily life. However, to the best of our knowledge, no previous studies have used electroencephalography (EEG) and galvanic skin response (GSR) together for boredom classification, although these data have potential features for emotion classification. To investigate the combined effect of these features on boredom classification, we collected EEG and GSR data from 28 participants using off-the-shelf sensors. During data acquisition, we used a set of stimuli comprising a video clip designed to elicit boredom and two other video clips of entertaining content. The collected samples were labeled based on the participants' questionnaire-based testimonies on experienced boredom levels. Using the collected data, we initially trained 30 models with 19 machine learning algorithms and selected the top three candidate classifiers. After tuning the hyperparameters, we validated the final models through 1000 iterations of 10-fold cross validation to increase the robustness of the test results. Our results indicated that a Multilayer Perceptron model performed the best with a mean accuracy of 79.98% (AUC: 0.781). It also revealed the correlation between boredom and the combined features of EEG and GSR. These results can be useful for building accurate affective computing systems and understanding the physiological properties of boredom.