The Influence of Unlimited Sucrose Intake on Body Weight and Behavior—Findings from a Mouse Model

A potential relationship between unrestricted sucrose intake (USI), overweight, and emotional/behavioral control has not been well documented. We examined the influence of USI and having less sweetness than expected on body weight (BW), motor/exploratory, anxiety-like, and social dominant behavior in adult C57BL/6J male mice. Animals had free access to water (group 1) or 32% sucrose and water (sucrose groups 2–5) for 10 days. Then, group 2 remained with 32% sucrose while groups 3–5 were subjected to the downshift (24 h access to 4%, 8%, or 16% sucrose). All experimental groups were weighed and tested in the novel-open arena (NA), elevated plus maze (EPM), and tube tests to assess BW, motor/exploratory, anxiety-like, and social dominance behavior, respectively. USI did not influence animals’ BW but produced hyperactivity and anxiolytic-like behavior, which was evident in EPM but not in NA; the outcomes of the downshift were comparable. USI did not influence successes/wins in the tube test but altered emotions that drive the winning, favoring a less anxious behavioral phenotype; this was not evident in the downshifted groups. Observed findings suggest that USI promotes sensation-seeking and motivates dominance, without changing BW, while blunted emotional base of social dominance might be an early mark of the downshift

Luck032/CardioPRINT-biometric-identification-with-machine-learning: CardioPRINT-biometric-identification-with-machine-learning

<p>This repository contains Python and R programming codes that reproduce results for the paper titled " CardioPRINT: Biometric identification based on the individual characteristics derived from cardiogram".</p><p>If you find provided code and signals useful for your own research and teaching class, please cite the following references:</p><ol><li>Tanasković, I., Lazarević, L. B., Knežević, G., Milosavljević, N., Dubljević, O., Bjegojević, B., & Miljković, N. (2023). CardioPRINT-based Biometric Identification with Machine Learning (Version 1.0) [Computer software]. <a href="https://github.com/Luck032/CardioPRINT-based-biometric-identification-with-machine-learning">https://github.com/Luck032/CardioPRINT-based-biometric-identification-with-machine-learning</a>, <a href="https://doi.org/10.5281/zenodo.10204894">https://doi.org/10.5281/zenodo.10204894</a></li><li>Tanasković, I., Lazarevic, L. B., Knezevic, G., Milosavljevic, N., Dubljević, O., Bjegojevic, B., & Miljković, N. (2023, November 24). CardioPRINT: Biometric identification based on the individual characteristics derived from cardiogram. PsyArXiv preprint. <a href="https://doi.org/10.31234/osf.io/bau7j">https://doi.org/10.31234/osf.io/bau7j</a></li><li>Bjegojević B, Milosavljević N, Dubljević O, Purić D, Knežević G. In pursuit of objectivity: Physiological Measures as a Means of Emotion Induction Procedure Validation. Empirical Studies in Psychology 2020:17.</li><li>Tanasković, I., Lazarević, L. B., Knežević, G., Milosavljević, N., Dubljević, O., Bjegojević, B., & Miljković, N. (2023). Dataset for CardioPRINT-based Biometric Identification [Dataset]. <a href="https://doi.org/10.5281/zenodo.10204955">https://doi.org/10.5281/zenodo.1020495</a></li></ol><p>Nadica Miljković acknowledges the support from Grant No. 451–03–47/ 2023–01/200103 funded by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia. </p><p>Ljiljana B. Lazarević and Goran Knežević acknowledge the support from Grant No. 451-03-47/2023-01/200163 funded by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia.</p&gt

CardioPRINT: Biometric identification based on the individual characteristics derived from cardiogram

Objective: This paper investigates the potential of cardiogram-derived traits from electrocardiogram (ECG) and impedance cardiogram (ICG) for biometric identification. Additionally, the influence of induced emotions on cardiogram attributes and their impact on identification accuracy is explored. Method: We conduct a comparative evaluation of 7 machine learning classifiers using dataset gathered from 202 individuals to identify the highest-performing classifiers. Subsequently, we analyze three different feature sets employing (ECG-only, ICG-only, and both ECG and ICG). Additionally, we investigate the performance of classifiers under altered emotional states to assess classifiers’ robustness. Results: The analysis demonstrates that models employed with both ECG and ICG have the highest accuracies that are statistically significant. The best-performing Random Forest (RF) model using both ECG and ICG achieves an average accuracy of 97.2%. All models reveal a decrease in classification accuracies (~13%) when they are not trained and tested under identical emotional conditions. Conclusion: Our findings suggest that integration of ECG and ICG-based features could increase the accuracy of identification compared to a single-signal-based approach. Although certain models show slight robustness to altered emotional state, the effect of the emotion is evident and future selection of cardiogram-based features, as well as biometric models, should consider emotional responses

Neuro‐immune interactions in health and disease: insights from FENS‐Hertie 2022 Winter School

In a great partnership, the Federation of European Neuroscience Societies (FENS) and the Hertie Foundation organized the FENS‐Hertie 2022 Winter School on ‘Neuro‐immune interactions in health and disease’. The school selected 27 PhD students and 13 postdoctoral fellows from 20 countries and involved 14 faculty members experts in the field. The Winter School focused on a rising field of research, the interactions between the nervous and both innate and adaptive immune systems under pathological and physiological conditions. A fine‐tuned neuro‐immune crosstalk is fundamental for healthy development, while disrupted neuro‐immune communication might play a role in neurodegeneration, neuroinflammation and aging. However, much is yet to be understood about the underlying mechanisms of these neuro‐immune interactions in the healthy brain and under pathological scenarios. In addition to new findings in this emerging field, novel methodologies and animal models were presented to foment research on neuro‐immunology. The FENS‐Hertie 2022 Winter School provided an insightful knowledge exchange between students and faculty focusing on the latest discoveries in the biology of neuro‐immune interactions while fostering great academic and professional opportunities for early‐career neuroscientists from around the world

Neuro‐immune interactions in health and disease: Insights from FENS‐Hertie 2022 Winter School

Abstract In a great partnership, the Federation of European Neuroscience Societies (FENS) and the Hertie Foundation organized the FENS‐Hertie 2022 Winter School on ‘Neuro‐immune interactions in health and disease’. The school selected 27 PhD students and 13 postdoctoral fellows from 20 countries and involved 14 faculty members experts in the field. The Winter School focused on a rising field of research, the interactions between the nervous and both innate and adaptive immune systems under pathological and physiological conditions. A fine‐tuned neuro‐immune crosstalk is fundamental for healthy development, while disrupted neuro‐immune communication might play a role in neurodegeneration, neuroinflammation and aging. However, much is yet to be understood about the underlying mechanisms of these neuro‐immune interactions in the healthy brain and under pathological scenarios. In addition to new findings in this emerging field, novel methodologies and animal models were presented to foment research on neuro‐immunology. The FENS‐Hertie 2022 Winter School provided an insightful knowledge exchange between students and faculty focusing on the latest discoveries in the biology of neuro‐immune interactions while fostering great academic and professional opportunities for early‐career neuroscientists from around the world

The Human Affectome

Over the last decades, the interdisciplinary field of the affective sciences has seen proliferation rather than integration of theoretical perspectives. This is due to differences in metaphysical and mechanistic assumptions about human affective phenomena (what they are and how they work) which, shaped by academic motivations and values, have determined the affective constructs and operationalizations. An assumption on the purpose of affective phenomena can be used as a teleological principle to guide the construction of a common set of metaphysical and mechanistic assumptions—a framework for human affective research. In this capstone paper for the special issue “Towards an Integrated Understanding of the Human Affectome”, we gather the tiered purpose of human affective phenomena to synthesize assumptions that account for human affective phenomena collectively. This teleologically-grounded framework offers a principled agenda and launchpad for both organizing existing perspectives and generating new ones. Ultimately, we hope Human Affectome brings us a step closer to not only an integrated understanding of human affective phenomena, but an integrated field for affective research

The Human Affectome

Over the last decades, the interdisciplinary field of the affective sciences has seen proliferation rather than integration of theoretical perspectives. This is due to differences in metaphysical and mechanistic assumptions about human affective phenomena (what they are and how they work) which, shaped by academic motivations and values, have determined the affective constructs and operationalizations. An assumption on the purpose of affective phenomenacan be used as a teleological principle to guide the construction of a common set of metaphysical and mechanistic assumptions—a framework for human affective research. In this capstone paper for the special issue “Towards an Integrated Understanding of the Human Affectome”, we gather the tiered purpose of human affective phenomena to synthesize assumptions that account for human affective phenomenacollectively. This teleologically-grounded framework offers a principled agenda and launchpad for both organizing existing perspectives and generating new ones. Ultimately, we hope Human Affectome brings us a step closer to not only an integrated understanding of human affective phenomena, but an integrated field for affective research

The Human Affectome

Over the last decades, the interdisciplinary field of the affective sciences has seen proliferation rather than integration of theoretical perspectives. This is due to differences in metaphysical and mechanistic assumptions about human affective phenomena (what they are and how they work) which, shaped by academic motivations and values, have determined the affective constructs and operationalizations. An assumption on the purpose of affective phenomena can be used as a teleological principle to guide the construction of a common set of metaphysical and mechanistic assumptions-a framework for human affective research. In this capstone paper for the special issue "Towards an Integrated Understanding of the Human Affectome", we gather the tiered purpose of human affective phenomena to synthesize assumptions that account for human affective phenomena collectively. This teleologically-grounded framework offers a principled agenda and launchpad for both organizing existing perspectives and generating new ones. Ultimately, we hope Human Affectome brings us a step closer to not only an integrated understanding of human affective phenomena, but an integrated field for affective research