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1. pH and redox triggered doxorubicin release from covalently linked carbon dots conjugates

   https://doi.org/10.1039/D0NR08381J  

   Hettiarachchi, Sajini D.; Kirbas Cilingir, Emel; Maklouf, Heidi; Seven, Elif S.; Paudyal, Suraj; Vanni, Steven; Graham, Regina M.; Leblanc, Roger M. (March 2021, Nanoscale)

   null (Ed.)

   Tumor microenvironment responsive drug delivery systems are potential approaches to reduce the acute toxicity caused by high-dose cancer chemotherapy. Notwithstanding the conventional nano-drug delivery systems, the redox and pH stimuli drug delivery systems are currently gaining attention. Therefore, the current study was designed to compare three different covalent carbon dots (C-dots) systems based on doxorubicin (dox) release profiles and cancer cell viability efficacy under acidic and physiological conditions. The C-dots nanosystems that were examined in this study are directly conjugated (C-dots-dox), pH triggered (C-dots-HBA-dox), and the redox stimuli (C-dots-S–S-dox) conjugates. The drug loading content (DLC%) of the C-dots-S–S-dox, C-dots-HBA-dox, and C-dots-dox was 34.2 ± 0.4, 60.0 ± 0.3, and 70.0 ± 0.2%, respectively, that examined by UV-vis spectral analysis. The dox release paradigms were emphasized that all three conjugates were promisingly released the dox from C-dots faster in acidic pH than in physiological pH. The displayed highest dox released percentage in the acidic medium was 74.6 ± 0.8% obtained by the pH stimuli, C-dots-HBA-dox conjugate. When introducing the redox inducer, dithiothreitol (DTT), preferentially, the redox stimuli C-dot-S–S-dox conjugate demonstrated a faster dox release at acidic pH than in the pH 7.4. The SJGBM2 cell viability experiments revealed that the pH stimuli, C-dots-HBA-dox conjugate, displayed a significant cell viability drop in the artificially acidified pH 6.4 medium. However, in the physiological pH, the redox stimuli, C-dots-S–S-dox conjugate, was promising over the pH stimuli C-dots-HBA-dox, exhibiting cell viability of 60%, though its’ efficacy dropped slightly in the artificially acidified pH 6.4 medium. Moreover, the current study illustrates the stimuli conjugates’ remarkable efficacy on sustain drug release than direct amide linkage. 

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2. Pupillary and microsaccadic responses to cognitive effort and emotional arousal during complex decision making

   https://doi.org/10.16910/jemr.13.5.2  

   Krejtz, Krzysztof; Żurawska, Justyna; Duchowski, Andrew; Wichary, Szymon (May 2020, Journal of eye movement research)

   A large body of literature documents the sensitivity of pupil response to cognitive load (e.g., Krejtz et al. 2018) and emotional arousal (Bradley et al., 2008). Recent empirical evidence also showed that microsaccade characteristics and dynamics can be modulated by mental fatigue and cognitive load (e.g., Dalmaso et al. 2017). Very little is known about the sensitivity of microsaccadic characteristics to emotional arousal. The present paper demonstrates in a controlled experiment pupillary and microsaccadic responses to information processing during multi-attribute decision making under affective priming. Twenty-one psychology students were randomly assigned into three affective priming conditions (neutral, aversive, and erotic). Participants were tasked to make several discriminative decisions based on acquired cues. In line with the expectations, results showed microsaccadic rate inhibition and pupillary dilation depending on cognitive effort (number of acquired cues) prior to decision. These effects were moderated by affective priming. Aversive priming strengthened pupillary and microsaccadic response to information processing effort. In general, results suggest that pupillary response is more biased by affective priming than microsaccadic rate. The results are discussed in the light of neuropsychological mechanisms of pupillary and microsaccadic behavior generation. 

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3. A Recurrent Neural Network for Attenuating Non-cognitive Components of Pupil Dynamics

   https://doi.org/10.3389/fpsyg.2021.604522  

   Koorathota, Sharath; Thakoor, Kaveri; Hong, Linbi; Mao, Yaoli; Adelman, Patrick; Sajda, Paul (February 2021, Frontiers in Psychology)

   null (Ed.)

   There is increasing interest in how the pupil dynamics of the eye reflect underlying cognitive processes and brain states. Problematic, however, is that pupil changes can be due to non-cognitive factors, for example luminance changes in the environment, accommodation and movement. In this paper we consider how by modeling the response of the pupil in real-world environments we can capture the non-cognitive related changes and remove these to extract a residual signal which is a better index of cognition and performance. Specifically, we utilize sequence measures such as fixation position, duration, saccades, and blink-related information as inputs to a deep recurrent neural network (RNN) model for predicting subsequent pupil diameter. We build and evaluate the model for a task where subjects are watching educational videos and subsequently asked questions based on the content. Compared to commonly-used models for this task, the RNN had the lowest errors rates in predicting subsequent pupil dilation given sequence data. Most importantly was how the model output related to subjects' cognitive performance as assessed by a post-viewing test. Consistent with our hypothesis that the model captures non-cognitive pupil dynamics, we found (1) the model's root-mean square error was less for lower performing subjects than for those having better performance on the post-viewing test, (2) the residuals of the RNN (LSTM) model had the highest correlation with subject post-viewing test scores and (3) the residuals had the highest discriminability (assessed via area under the ROC curve, AUC) for classifying high and low test performers, compared to the true pupil size or the RNN model predictions. This suggests that deep learning sequence models may be good for separating components of pupil responses that are linked to luminance and accommodation from those that are linked to cognition and arousal. 

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4. Dynamics of emotional facial expression recognition in individuals with social anxiety

   https://doi.org/10.1145/3204493.3204533  

   Krejtz, Krzysztof; Wisiecka, Katarzyna; Krejtz, Izabela; Holas, Paweł; Olszanowski, Michał; Duchowski, Andrew T. (June 2018, Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications (ETRA '18))

   This paper demonstrates the utility of ambient-focal attention and pupil dilation dynamics to describe visual processing of emotional facial expressions. Pupil dilation and focal eye movements reflect deeper cognitive processing and thus shed more light on the dy- namics of emotional expression recognition. Socially anxious in- dividuals (N = 24) and non-anxious controls (N = 24) were asked to recognize emotional facial expressions that gradually morphed from a neutral expression to one of happiness, sadness, or anger in 10-sec animations. Anxious cohorts exhibited more ambient face scanning than their non-anxious counterparts. We observed a positive relationship between focal fixations and pupil dilation, indi- cating deeper processing of viewed faces, but only by non-anxious participants, and only during the last phase of emotion recognition. Group differences in the dynamics of ambient-focal attention sup- port the hypothesis of vigilance to emotional expression processing by socially anxious individuals. We discuss the results by referring to current literature on cognitive psychopathology. 

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5. Spectral signature and behavioral consequence of spontaneous shifts of pupil-linked arousal in human

   https://doi.org/10.7554/eLife.68265  

   Podvalny, Ella; King, Leana E; He, Biyu J (August 2021, eLife)

   Arousal levels perpetually rise and fall spontaneously. How markers of arousal—pupil size and frequency content of brain activity—relate to each other and influence behavior in humans is poorly understood. We simultaneously monitored magnetoencephalography and pupil in healthy volunteers at rest and during a visual perceptual decision-making task. Spontaneously varying pupil size correlates with power of brain activity in most frequency bands across large-scale resting state cortical networks. Pupil size recorded at prestimulus baseline correlates with subsequent shifts in detection bias ( c ) and sensitivity ( d ’). When dissociated from pupil-linked state, prestimulus spectral power of resting state networks still predicts perceptual behavior. Fast spontaneous pupil constriction and dilation correlate with large-scale brain activity as well but not perceptual behavior. Our results illuminate the relation between central and peripheral arousal markers and their respective roles in human perceptual decision-making. 

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