Monitoring mental workload by EEG during a game in Virtual Reality

During an activity, knowing the mental workload (MWL) of the user allows to improve the Human-Machine Interactions (HMI). Indeed, the MWL has an impact on the individual and its interaction with the environment. Monitoring it is therefore a crucial issue. In this context, we have created the virtual game Back to Pizza which is based on the N-back task (commonly used for measuring MWL). In this more playful variant, users must carry out orders from customers of a pizza food truck. It is an interactive game that involves the audience of the IHM'23 conference, choosing several parameters like the number of ingredients. During this experience, the objective is to measure MWL in real time through an ElectroEncephaloGraph (EEG) and visual feedback on MWL level is given to the audience. With this demonstration, we propose to present a concept of a virtual interactive game that measures MWL in real time.Comment: IHM'23 - 34e Conf{\'e}rence Internationale Francophone sur l'Interaction Humain-Machine, AFIHM; Universit{\'e} de Technologie de Troyes, Apr 2023, Troyes, Franc

Cabbage and fermented vegetables : From death rate heterogeneity in countries to candidates for mitigation strategies of severe COVID-19

Large differences in COVID-19 death rates exist between countries and between regions of the same country. Some very low death rate countries such as Eastern Asia, Central Europe, or the Balkans have a common feature of eating large quantities of fermented foods. Although biases exist when examining ecological studies, fermented vegetables or cabbage have been associated with low death rates in European countries. SARS-CoV-2 binds to its receptor, the angiotensin-converting enzyme 2 (ACE2). As a result of SARS-CoV-2 binding, ACE2 downregulation enhances the angiotensin II receptor type 1 (AT(1)R) axis associated with oxidative stress. This leads to insulin resistance as well as lung and endothelial damage, two severe outcomes of COVID-19. The nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is the most potent antioxidant in humans and can block in particular the AT(1)R axis. Cabbage contains precursors of sulforaphane, the most active natural activator of Nrf2. Fermented vegetables contain many lactobacilli, which are also potent Nrf2 activators. Three examples are: kimchi in Korea, westernized foods, and the slum paradox. It is proposed that fermented cabbage is a proof-of-concept of dietary manipulations that may enhance Nrf2-associated antioxidant effects, helpful in mitigating COVID-19 severity.Peer reviewe

Nrf2-interacting nutrients and COVID-19 : time for research to develop adaptation strategies

There are large between- and within-country variations in COVID-19 death rates. Some very low death rate settings such as Eastern Asia, Central Europe, the Balkans and Africa have a common feature of eating large quantities of fermented foods whose intake is associated with the activation of the Nrf2 (Nuclear factor (erythroid-derived 2)-like 2) anti-oxidant transcription factor. There are many Nrf2-interacting nutrients (berberine, curcumin, epigallocatechin gallate, genistein, quercetin, resveratrol, sulforaphane) that all act similarly to reduce insulin resistance, endothelial damage, lung injury and cytokine storm. They also act on the same mechanisms (mTOR: Mammalian target of rapamycin, PPAR gamma:Peroxisome proliferator-activated receptor, NF kappa B: Nuclear factor kappa B, ERK: Extracellular signal-regulated kinases and eIF2 alpha:Elongation initiation factor 2 alpha). They may as a result be important in mitigating the severity of COVID-19, acting through the endoplasmic reticulum stress or ACE-Angiotensin-II-AT(1)R axis (AT(1)R) pathway. Many Nrf2-interacting nutrients are also interacting with TRPA1 and/or TRPV1. Interestingly, geographical areas with very low COVID-19 mortality are those with the lowest prevalence of obesity (Sub-Saharan Africa and Asia). It is tempting to propose that Nrf2-interacting foods and nutrients can re-balance insulin resistance and have a significant effect on COVID-19 severity. It is therefore possible that the intake of these foods may restore an optimal natural balance for the Nrf2 pathway and may be of interest in the mitigation of COVID-19 severity

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Effect of Task Ludification on Subjective Responses to Mental Workload During Digitalized Cognitive Task.

Cognitive tasks usually used in rehabilitation or evaluation of cognitive functions are viewed as effortful or frustrating, which often leads to participant disengagement and high mental workload (MWL). The challenge is to increase the task’s commitment while decreasing MWL and maintaining similar impact on cognitive functions. Introducing playfulness could decrease the part of MWL due to endogenous factors (like demotivation) without affecting the task’s cognitive aspect. Nevertheless, there is no study investigating the link between ludification, commitment, and MWL and the performance’s repercussions. Therefore, we developed a protocol to compare the subjective MWL for three conditions of a cognitive task that differed depending on the degree of ludification. Overall, our results showed that performances were not influenced by ludification, confirming that it did not reduce the effects on cognitive functions solicited during the task. Regarding the impact on engagement and MWL, it will be discussed in light of different models of MWL

Subjective mental workload modeling in tests involving different cognitive functions

Over time, mental workload (MWL) has become a major topic of scientific discussions. Nevertheless, there is no reference model involving standardized cognitive tests with distinct levels of difficulty and allowing to consider the correlation between task performance and MWL based on these levels. Therefore, we have developed an innovative protocol to model the variation of self-reported MWL (via the NASA-TLX and Workload Profile questionnaires) for tests requiring different cognitive functions (memory, mental inhibition, mental flexibility, and divided attention). Each of these tasks is an adaptation of existing cognitive tests, for which three equivalent difficulty levels were established in terms of impact on performance.The results showed that our difficulty levels allowed distinct classes of MWL and that it co-varied negatively with the performance across difficulty. Our protocol has thus provided new benchmarks that can be useful in many domains where it’s essential to be able to infer MWL from test performance

Inter-tasks transferability of a subjective cognitive load classification model

Studying cognitive load (CL) presents several challenges, including the need for accurate and generic CL classification models. Previous studies have solely relied on physiological data to measure CL, as in Appel et al. (2021). However, what about subjective CL measure?Thus, we proposed a three-class classification model of subjective CL through five cognitive tasks: N-back, Corsi, Go/No-Go, WCST, and Dual task (Louis et al. 2023). For this conference, we examined whether a model trained on a Task A could accurately predict the subjective CL classes of a Task B.Firstly, the results showed that Corsi was the most effective task for classifying subjective CL based only on performance and complexity levels, achieving 80% accuracy. Moreover, a classification model trained on N-back, WCST, and Dual task could predict the subjective CL classes of Corsi with over 70% accuracy. This perspective would save time in setting up and training a classification model

Cognitive tasks and combined statistical methods to evaluate, model, and predict mental workload

Mental workload (MWL) is a concept that is used as a reference for assessing the mental cost of activities. In recent times, challenges related to user experience are determining the expected MWL value for a given activity and real-time adaptation of task complexity level to achieve or maintain desired MWL. As a consequence, it is important to have at least one task that can reliably predict the MWL level associated with a given complexity level. In this study, we used several cognitive tasks to meet this need, including the N-Back task, the commonly used reference test in the MWL literature, and the Corsi test. Tasks were adapted to generate different MWL classes measured via NASA-TLX and Workload Profile questionnaires. Our first objective was to identify which tasks had the most distinct MWL classes based on combined statistical methods. Our results indicated that the Corsi test satisfied our first objective, obtaining three distinct MWL classes associated with three complexity levels offering therefore a reliable model (about 80% accuracy) to predicted MWL classes. Our second objective was to achieve or maintain the desired MWL, which entailed the use of an algorithm to adapt the MWL class based on an accurate prediction model. This model needed to be based on an objective and real-time indicator of MWL. For this purpose, we identified different performance criteria for each task. The classification models obtained indicated that only the Corsi test would be a good candidate for this aim (more than 50% accuracy compared to a chance level of 33%) but performances were not sufficient to consider identifying and adapting the MWL class online with sufficient accuracy during a task. Thus, performance indicators require to be complemented by other types of measures like physiological ones. Our study also highlights the limitations of the N-back task in favor of the Corsi test which turned out to be the best candidate to model and predict the MWL among several cognitive tasks

The PRSS3P2 and TRY7 deletion copy number variant modifies risk for chronic pancreatitis

Background PRSS1 and PRSS2 constitute the only functional copies of a tandemly-arranged five-trypsinogen-gene cluster (i.e., PRSS1, PRSS3P1, PRSS3P2, TRY7 and PRSS2) on chromosome 7q35. Variants in PRSS1 and PRSS2, including missense and copy number variants (CNVs), have been reported to predispose to or protect against chronic pancreatitis (CP). We wondered whether a common trypsinogen pseudogene deletion CNV (that removes two of the three trypsinogen pseudogenes, PRSS3P2 and TRY7) might be associated with CP causation/predisposition. Methods We analyzed the common PRSS3P2 and TRY7 deletion CNV in a total of 1536 CP patients and 3506 controls from France, Germany, India and Japan by means of quantitative fluorescent multiplex polymerase chain reaction. Results We demonstrated that the deletion CNV variant was associated with a protective effect against CP in the French, German and Japanese cohorts whilst a trend toward the same association was noted in the Indian cohort. Meta-analysis under a dominant model yielded a pooled odds ratio (OR) of 0.68 (95% confidence interval (CI) 0.52–0.89; p = 0.005) whereas an allele-based meta-analysis yielded a pooled OR of 0.84 (95% CI 0.77–0.92; p = 0.0001). This protective effect is explicable by reference to the recent finding that the still functional PRSS3P2/TRY7 pseudogene enhancers upregulate pancreatic PRSS2 expression. Conclusions The common PRSS3P2 and TRY7 deletion CNV was associated with a reduced risk for CP. This finding provides additional support for the emerging view that dysregulated PRSS2 expression represents a discrete mechanism underlying CP predisposition or protection

The PRSS3P2 and TRY7 deletion copy number variant modifies risk for chronic pancreatitis

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