Prepubertal gonad investment modulates thymus function: evidence in a teleost fish.

Thymus plasticity following gonadectomy or sex hormone replacement has long since exemplified sex hormone effects on the immune system in mammals and, to a lesser extent, in 'lower vertebrates', including amphibians and fish. Nevertheless, the underlying physiological significances as well as the ontogenetic establishment of this crosstalk remain largely unknown. Here, we used a teleost fish, the European sea bass, Dicentrarchus labrax, to investigate: (1) whether the regulation of thymus plasticity relies on resource trade-off with somatic growth and reproductive investment and (2) if the gonad-thymus interaction takes place during gonadal differentiation and development. Because gonadal development and, supposedly, thymus function in sea bass depend on environmental changes associated with the winter season, we evaluated thymus changes (foxn1 expression, and thymocyte and T cell content) in juvenile D. labrax raised for 1 year under either constant or fluctuating photoperiod and temperature. Importantly, in both conditions, intensive gonadal development following sex differentiation coincided with a halt of thymus growth, while somatic growth continued. To the best of our knowledge, this is the first study showing that gonadal development during prepuberty regulates thymus plasticity. This finding may provide an explanation for the initiation of the thymus involution related to ageing in mammals. Comparing fixed and variable environmental conditions, our work also demonstrates that the extent of the effects on the thymus, which are related to reproduction, depend on ecophysiological conditions, rather than being directly related to sexual maturity and sex hormone levels.

Prepubertal gonad investment modulates thymus function: evidence in a teleost fish.

Thymus plasticity following gonadectomy or sex hormone replacement has long since exemplified sex hormone effects on the immune system in mammals and, to a lesser extent, in 'lower vertebrates', including amphibians and fish. Nevertheless, the underlying physiological significances as well as the ontogenetic establishment of this crosstalk remain largely unknown. Here, we used a teleost fish, the European sea bass, Dicentrarchus labrax, to investigate: (1) whether the regulation of thymus plasticity relies on resource trade-off with somatic growth and reproductive investment and (2) if the gonad-thymus interaction takes place during gonadal differentiation and development. Because gonadal development and, supposedly, thymus function in sea bass depend on environmental changes associated with the winter season, we evaluated thymus changes (foxn1 expression, and thymocyte and T cell content) in juvenile D. labrax raised for 1 year under either constant or fluctuating photoperiod and temperature. Importantly, in both conditions, intensive gonadal development following sex differentiation coincided with a halt of thymus growth, while somatic growth continued. To the best of our knowledge, this is the first study showing that gonadal development during prepuberty regulates thymus plasticity. This finding may provide an explanation for the initiation of the thymus involution related to ageing in mammals. Comparing fixed and variable environmental conditions, our work also demonstrates that the extent of the effects on the thymus, which are related to reproduction, depend on ecophysiological conditions, rather than being directly related to sexual maturity and sex hormone levels.

Transcriptomic response of the intertidal limpet Patella vulgata to temperature extremes.

Global warming is challenging wild species in land and water. In the intertidal zone, species are already living at their thermal limits, being vulnerable even to small increases in maximum habitat temperatures. Knowledge of the mechanisms by which many intertidal zone species cope with elevated temperatures is limited. We analysed the molecular thermal stress response of the limpet Patella vulgata under slight and frequent (one-day), and extreme and rare (three-day) warming events. Using RNA-seq to assess differential gene expression among treatments, differing molecular responses were obtained in the two treatments, with more changes in gene expression after the three-day event; with one-third of the differentially expressed transcripts being down-regulated. However, across treatments we observed shifts in gene expression for common aspects of the heat stress response including intra-cellular communication, protein chaperoning, proteolysis and cell cycle arrest. Of the 71,675 transcripts obtained, only 259 were differentially expressed after both heating events. From these, 218 defined the core group (i.e. genes induced by thermal stress with similar expression patterns irrespective of the magnitude of the warming event). The core group was composed of already well-studied genes in heat stress responses in intertidal organisms (e.g. heat shock proteins), but also genes from less explored metabolic pathways, e.g. the ubiquitin system, which were also fundamental regardless of the magnitude of the imposed warming. Moreover, we have also identified 41 signaling genes (i.e. a set of genes responding to both events and with expression patterns specific to the intensity of thermal stress), principally including genes involved in the maintenance of extracellular structure that have previously not been identified as part of the response to thermal stress in intertidal zone organisms. These signaling genes will be useful heat stress molecular biomarkers for monitoring heat stress in natural populations.

Towards a quantum-like cognitive architecture for decision-making.

We propose an alternative and unifying framework for decision-making that, by using quantum mechanics, provides more generalised cognitive and decision models with the ability to represent more information compared to classical models. This framework can accommodate and predict several cognitive biases reported in Lieder & Griffiths without heavy reliance on heuristics or on assumptions of the computational resources of the mind.

Balanced Quantum-Like Bayesian Networks.

Empirical findings from cognitive psychology indicate that, in scenarios under high levels of uncertainty, many people tend to make irrational decisions. To address this problem, models based on quantum probability theory, such as the quantum-like Bayesian networks, have been proposed. However, this model makes use of a Bayes normalisation factor during probabilistic inference to convert the likelihoods that result from quantum interference effects into probability values. The interpretation of this operation is not clear and leads to extremely skewed intensity waves that make the task of prediction of these irrational decisions challenging. This article proposes the law of balance, a novel mathematical formalism for probabilistic inferences in quantum-like Bayesian networks, based on the notion of balanced intensity waves. The general idea is to balance the intensity waves resulting from quantum interference in such a way that, during Bayes normalisation, they cancel each other. With this representation, we also propose the law of maximum uncertainty, which is a method to predict these paradoxes by selecting the amplitudes of the wave with the highest entropy. Empirical results show that the law of balance together with the law of maximum uncertainty were able to accurately predict different experiments from cognitive psychology showing paradoxical or irrational decisions, namely in the Prisoner's Dilemma game and the Two-Stage Gambling Game.

Oestrogen differentially modulates lymphoid and myeloid cells of the European sea bass in vitro by specifically regulating their redox biology.

Besides their obvious role in sex determination and reproduction, oestrogens display a prominent and complex immunomodulatory role across all vertebrates. To date, our knowledge on the oestrogenic immunomodulation in non-mammalian species is, however, scarce. In both teleosts and mammals, the direct immunomodulatory function of oestrogen is underscored by the presence of multiple oestrogen receptor subtypes in the various immune cells. For a better understanding of the regulatory processes, we investigated the oestrogen receptor expression in two major lymphoid organs of European sea bass: the head-kidney and the spleen. All oestrogen receptor subtypes, including nuclear and membrane oestrogen receptors, were present in both immune organs as well as in the isolated leucocytes. The same findings have been previously made for the thymus. To determine the oestrogen responsiveness of the different immune cell populations and to evaluate the importance of non-genomic and genomic pathways, we assessed the kinetics and the concentration dependent effects of 17ß-oestradiol on isolated leucocytes from the head-kidney, the spleen and the thymus in vitro. Given the importance of reactive oxygen species as signalling and defence components in mammalian immune cells, the oxidative burst capacity, the redox status and the viability of both lymphoid and myeloid cells were measured by flow cytometry. The treatment with 17ß-oestradiol specifically modulated these parameters depending on (1) the time kinetic, (2) the concentration of 17ß-oestradiol, (3) the immune cell population (lymphoid and myeloid cells) as well as (4) the lymphoid organs from which they originated. The observed in vitro oestrogenic effects as well the presence of various oestrogen receptor subtypes in the immune cells of sea bass suggest a complex and direct oestrogenic action via multiple interconnected oestrogen-signalling pathways. Additionally, our study suggests that the oestrogenic regulation of the sea bass immune function involves a direct and tissue specific modulation of the immune cell redox biology comprising redox signalling, NADPH-oxidase activity and H2O2-permeability, thus changing oxidative burst capacity and immature T cell fate because oestrogen impacted thymocyte viability. Importantly, immune cells from both primary and secondary lymphoid organs have shown specific in vitro oestrogen-responsiveness. As established in mammals, oestrogen is likely to be specifically and directly involved in immature T cell differentiation and mature immunocompetent cell function in sea bass too.

Intelligent systems in healthcare: A systematic survey of explainable user interfaces.

With radiology shortages affecting over half of the global population, the potential of artificial intelligence to revolutionize medical diagnosis and treatment is ever more important. However, lacking trust from medical professionals hinders the widespread adoption of AI models in health sciences. Explainable AI (XAI) aims to increase trust and understanding of black box models by identifying biases and providing transparent explanations. This is the first survey that explores explainable user interfaces (XUI) from a medical domain perspective, analysing the visualization and interaction methods employed in current medical XAI systems. We analysed 42 explainable interfaces following the PRISMA methodology, emphasizing the critical role of effectively conveying information to users as part of the explanation process. We contribute a taxonomy of interface design properties and identify five distinct clusters of research papers. Future research directions include contestability in medical decision support, counterfactual explanations for images, and leveraging Large Language Models to enhance XAI interfaces in healthcare.

Evolutionary history and functional characterization of duplicated G protein-coupled estrogen receptors in European sea bass.

Across vertebrates, the numerous estrogenic functions are mainly mediated by nuclear and membrane receptors, including the G protein-coupled estrogen receptor (GPER) that has been mostly associated with rapid non-genomic responses. Although Gper-mediated signalling has been characterized in only few fish species, Gpers in fish appear to present more mechanistic functionalities as those of mammals due to additional gene duplicates. In this study, we ran a thorough investigation of the fish Gper evolutionary history in light of available genomes, we carried out the functional characterization of the two gper gene duplicates of European sea bass (Dicentrarchus labrax) using luciferase reporter gene transactivation assays, validated it with natural and synthetic estrogen agonists/antagonists and applied it to other chemicals of aquaculture and ecotoxicological interest. Phylogenetic and synteny analyses of fish gper1 and gper1-like genes suggest their duplication may have not resulted from the teleost-specific whole genome duplication. We confirmed that both sbsGper isoforms activate the cAMP signalling pathway and respond differentially to distinct estrogenic compounds. Therefore, as observed for nuclear estrogen receptors, both sbsGpers duplicates retain estrogenic activity although they differ in their specificity and potency (Gper1 being more potent and more specific than Gper1-like), suggesting a more conserved role for Gper1 than for Gper1-like. In addition, Gpers were able to respond to estrogenic environmental pollutants known to interfere with estrogen signalling, such as the phytoestrogen genistein and the anti-depressant fluoxetine, a point that can be taken into account in aquatic environment pollution screenings and chemical risk assessment, complementing previous assays for sea bass nuclear estrogen receptors.

Shedding light on ai in radiology: A systematic review and taxonomy of eye gaze-driven interpretability in deep learning.

X-ray imaging plays a crucial role in diagnostic medicine. Yet, a significant portion of the global population lacks access to this essential technology due to a shortage of trained radiologists. Eye-tracking data and deep learning models can enhance X-ray analysis by mapping expert focus areas, guiding automated anomaly detection, optimizing workflow efficiency, and bolstering training methods for novice radiologists. However, the literature shows contradictory results regarding the usefulness of eye-tracking data in deep-learning architectures for abnormality detection. We argue that these discrepancies between studies in the literature are due to (a) the way eye-tracking data is (or is not) processed, (b) the types of deep learning architectures chosen, and (c) the type of application that these architectures will have. We conducted a systematic literature review using PRISMA to address these contradicting results. We analyzed 60 studies that incorporated eye-tracking data in a deep-learning approach for different application goals in radiology. We performed a comparative analysis to understand if eye gaze data contains feature maps that can be useful under a deep learning approach and whether they can promote more interpretable predictions. To the best of our knowledge, this is the first survey in the area that performs a thorough investigation of eye gaze data processing techniques and their impacts in different deep learning architectures for applications such as error detection, classification, object detection, expertise level analysis, fatigue estimation and human attention prediction in medical imaging data. Our analysis resulted in two main contributions: (1) taxonomy that first divides the literature by task, enabling us to analyze the value eye movement can bring for each case and build guidelines regarding architectures and gaze processing techniques adequate for each application, and (2) an overall analysis of how eye gaze data can promote explainability in radiology.

Comprehensive review of deep learning in orthopaedics: Applications, challenges, trustworthiness, and fusion.

Deep learning (DL) in orthopaedics has gained significant attention in recent years. Previous studies have shown that DL can be applied to a wide variety of orthopaedic tasks, including fracture detection, bone tumour diagnosis, implant recognition, and evaluation of osteoarthritis severity. The utilisation of DL is expected to increase, owing to its ability to present accurate diagnoses more efficiently than traditional methods in many scenarios. This reduces the time and cost of diagnosis for patients and orthopaedic surgeons. To our knowledge, no exclusive study has comprehensively reviewed all aspects of DL currently used in orthopaedic practice. This review addresses this knowledge gap using articles from Science Direct, Scopus, IEEE Xplore, and Web of Science between 2017 and 2023. The authors begin with the motivation for using DL in orthopaedics, including its ability to enhance diagnosis and treatment planning. The review then covers various applications of DL in orthopaedics, including fracture detection, detection of supraspinatus tears using MRI, osteoarthritis, prediction of types of arthroplasty implants, bone age assessment, and detection of joint-specific soft tissue disease. We also examine the challenges for implementing DL in orthopaedics, including the scarcity of data to train DL and the lack of interpretability, as well as possible solutions to these common pitfalls. Our work highlights the requirements to achieve trustworthiness in the outcomes generated by DL, including the need for accuracy, explainability, and fairness in the DL models. We pay particular attention to fusion techniques as one of the ways to increase trustworthiness, which have also been used to address the common multimodality in orthopaedics. Finally, we have reviewed the approval requirements set forth by the US Food and Drug Administration to enable the use of DL applications. As such, we aim to have this review function as a guide for researchers to develop a reliable DL application for orthopaedic tasks from scratch for use in the market.

MDF-Net for abnormality detection by fusing X-rays with clinical data.

This study investigates the effects of including patients' clinical information on the performance of deep learning (DL) classifiers for disease location in chest X-ray images. Although current classifiers achieve high performance using chest X-ray images alone, consultations with practicing radiologists indicate that clinical data is highly informative and essential for interpreting medical images and making proper diagnoses. In this work, we propose a novel architecture consisting of two fusion methods that enable the model to simultaneously process patients' clinical data (structured data) and chest X-rays (image data). Since these data modalities are in different dimensional spaces, we propose a spatial arrangement strategy, spatialization, to facilitate the multimodal learning process in a Mask R-CNN model. We performed an extensive experimental evaluation using MIMIC-Eye, a dataset comprising different modalities: MIMIC-CXR (chest X-ray images), MIMIC IV-ED (patients' clinical data), and REFLACX (annotations of disease locations in chest X-rays). Results show that incorporating patients' clinical data in a DL model together with the proposed fusion methods improves the disease localization in chest X-rays by 12% in terms of Average Precision compared to a standard Mask R-CNN using chest X-rays alone. Further ablation studies also emphasize the importance of multimodal DL architectures and the incorporation of patients' clinical data in disease localization. In the interest of fostering scientific reproducibility, the architecture proposed within this investigation has been made publicly accessible( https://github.com/ChihchengHsieh/multimodal-abnormalities-detection ).

An Extension of Combinatorial Contextuality for Cognitive Protocols.

This article extends the combinatorial approach to support the determination of contextuality amidst causal influences. Contextuality is an active field of study in Quantum Cognition, in systems relating to mental phenomena, such as concepts in human memory. In the cognitive field of study, a contemporary challenge facing the determination of whether a phenomenon is contextual has been the identification and management of disturbances. Whether or not said disturbances are identified through the modeling approach, constitute causal influences, or are disregardableas as noise is important, as contextuality cannot be adequately determined in the presence of causal influences. To address this challenge, we first provide a formalization of necessary elements of the combinatorial approach within the language of canonical causal models. Through this formalization, we extend the combinatorial approach to support a measurement and treatment of disturbance, and offer techniques to separately distinguish noise and causal influences. Thereafter, we develop a protocol through which these elements may be represented within a cognitive experiment. As human cognition seems rife with causal influences, cognitive modelers may apply the extended combinatorial approach to practically determine the contextuality of cognitive phenomena.

Proteomic changes in the extracellular environment of sea bass thymocytes exposed to 17α-ethinylestradiol in vitro.

The thymus is an important immune organ providing the necessary microenvironment for the development of a diverse, self-tolerant T cell repertoire, which is selected to allow for the recognition of foreign antigens while avoiding self-reactivity. Thymus function and activity are known to be regulated by sex steroid hormones, such as oestrogen, leading to sexual dimorphisms in immunocompetence between males and females. The oestrogenic modulation of the thymic function provides a potential target for environmental oestrogens, such as 17α-ethynylestradiol (EE2), to interfere with the cross-talk between the endocrine and the immune system. Oestrogen receptors have been identified on thymocytes and the thymic microenvironment, but it is unclear how oestrogens regulate thymic epithelial and T cell communication including paracrine signalling. Much less is known regarding intrathymic signalling in fish. Secretomics allows for the analysis of complex mixtures of immunomodulatory signalling factors secreted by T cells. Thus, in the present study, isolated thymocytes of the European sea bass, Dicentrarchus labrax, were exposed in vitro to 30 nM EE2 for 4 h and the T cell-secretome (i.e., extracellular proteome) was analysed by quantitative label-free mass-spectrometry. Progenesis revealed a total of 111 proteins differentially displayed between EE2-treated and control thymocytes at an α-level of 5% and a 1.3-fold change cut off (n = 5-6). The EE2-treatment significantly decreased the level of 90 proteins. Gene ontology revealed the proteasome to be the most impacted pathway. In contrast, the abundance of 21 proteins was significantly increased, with cathepsins showing the highest level of induction. However, no particular molecular pathway was significantly altered for these upregulated proteins. To the best of our knowledge, this work represents the first study of the secretome of the fish thymus exposed to the environmental oestrogen EE2, highlighting the impact on putative signalling pathways linked to immune surveillance, which may be of crucial importance for fish health and defence against pathogens.

The influence of 17ß-oestradiol on lymphopoiesis and immune system ontogenesis in juvenile sea bass, Dicentrarchus labrax.

The female sex steroid 17ß-oestradiol (E2) is involved in the regulation of numerous physiological functions, including the immune system development and performance. The role of oestrogens during ontogenesis is, however, not well studied. In rodents and fish, thymus maturation appears to be oestrogen-dependent. Nevertheless, little is known about the function of oestrogen in immune system development. To further the understanding of the role of oestrogens in fish immune system ontogenesis, fingerlings of European sea bass (Dicentrarchus labrax) were exposed for 30 days to 20 ng E2·L-1, at two ages tightly related to thymic maturation, i.e., 60 or 90 days post hatch (dph). The expression of nuclear and membrane oestrogen receptors was measured in the thymus and spleen, and the expression of several T cell-related gene markers was studied in both immune organs, as well as in the liver. Waterborne E2-exposure at 20.2 ± 2.1 (S.E.) ng·L-1 was confirmed by radioimmunoassay, leading to significantly higher E2-contents in the liver of exposed fish. The majority of gene markers presented age-dependent dynamics in at least one of the organs, confirming thymus maturation, but also suggesting a critical ontogenetic window for the implementation of liver resident γδ and αß T cells. The oestrogen receptors, however, remained unchanged over the age and treatment comparisons with the exception of esr2b, which was modulated by E2 in the younger cohort and increased its expression with age in the thymus of the older cohort, as did the membrane oestrogen receptor gpera. These results confirm that oestrogen-signalling is involved in thymus maturation in European sea bass, as it is in mammals. This suggests that esr2b and gpera play key roles during thymus ontogenesis, particularly during medulla maturation. In contrast, the spleen expressed low or non-detectable levels of oestrogen receptors. The E2-exposure decreased the expression of tcrγ in the liver in the cohort exposed from 93 to 122 dph, but not the expression of any other immune-related gene analysed. These results indicate that the proliferation/migration of these innate-like T cell populations is oestrogen-sensitive. In regard to the apparent prominent role of oestrogen-signalling in the late thymus maturation stage, the thymic differentiation of the corresponding subpopulations of T cells might be regulated by oestrogen. To the best of our knowledge, this is the first study investigating the dynamics of both nuclear and membrane oestrogen receptors in specific immune organs in a teleost fish at very early stages of immune system development as well as to examine thymic function in sea bass after an exposure to E2 during ontogenesis.

Algal proteins: Production strategies and nutritional and functional properties.

Animal-based proteins are the most consumed worldwide given their well-balanced nutritional composition. However, the growing demand for animal proteins will not be sustainable due to their low conversion efficiency and high environmental footprint. Specific consumers' dietary restrictions and modern trends emphasize the importance of finding alternative sustainable non-animal sources to meet future food (and, in particular, protein) global needs. Algal biomass is considered a relevant alternative, presenting advantages over terrestrial biomass such as higher growth rate, low water consumption, no competition for arable land, carbon-neutral emissions, and production of numerous bioactive compounds. This review provides an overview of recent research advances on algae as source of proteins, including production strategies from relevant protein-producing species. Particular emphasis will be given to algae protein current applications and forthcoming challenges of their use. Nutritional and functional aspects of algae biomass or its protein-enriched fractions will be overviewed.

Tracheobronchopathia Osteochondroplastica: Two Different Facets of a Rare Entity.

Tracheobronchopathia osteochondroplastica (TBPO) is an uncommon benign disease, characterized by osseous or metaplastic cartilaginous nodules in the submucosa of the tracheobronchial tree. TBPO is easy to misdiagnose due to its non-specific clinical manifestation. We describe two cases of TBPO. The first patient was a 57-year-old woman with nocturnal dry cough and wheezing, in whom bronchoscopy revealed small diffuse mucosal irregularities involving the airway until the segmental bronchi. The other patient was a 69-year-old man with progressive worsening dyspnoea and productive cough presenting with severe stenosis of the trachea. Histological examination of both cases was consistent with TBPO. These cases highlight distinct forms of presentation of this rare entity. LEARNING POINTS: Tracheobronchopathia osteochondroplastica (TBPO) can present as a diffuse large airway disease with mild obstructive symptoms or as severe tracheal obstruction.Direct observation by bronchial fibroscopy of lumen protrusions sparing the posterior wall is diagnostic.

Sarcoidosis related to checkpoint and BRAF/MEK inhibitors in melanoma.

Therapy for advanced melanoma has deeply changed in the last decade with the introduction of checkpoint and BRAF/MEK inhibitors. Granulomatous reactions have been reported related to these drugs. We performed a systematic review of all the cases described in the medical literature by the search (("Melanoma"[Mesh]) AND ("Sarcoidosis"[Mesh] OR "Granuloma"[Mesh])). Ninety-one patients under immunotherapy were included in the analyses. The time from the initiation of the immunotherapy until the onset of sarcoidosis or sarcoid-like reaction (SLR) was 7.1 months (SD 9). Peripheral lymph nodes as the mode of onset were seen more frequently in patients under CTLA-4 inhibitors (p = .016) whereas in patients under BRAF/MEK inhibitors used to be in the form of specific skin lesions (p = .006). Chest X-ray stage I-II was the rule in the CTLA-4 and PD-1 groups. On the contrary, stage 0 accounted for 80% of the patients in the BRAF/MEK group examined for pulmonary involvement. Specific skin involvement was the most common manifestation apart from pulmonary involvement. It was more frequent in patients under BRAF/MEK inhibitors and especially in the form of papules. Splenic involvement was found also more frequently in patients under CTLA-4 inhibitors. Specific treatment for sarcoidosis/SLR was prescribed in 50 patients (58.8%), without differences among groups. Almost all patients presented a good prognosis independently of the decision made regarding their previous immunotherapy. CONCLUSION: Physicians should bear in mind the possibility of sarcoidosis/SLR after the initiation of checkpoint or BRAF/MEK inhibitors in patients diagnosed with advanced melanoma, especially in the form of skin involvement and mediastinal and peripheral lymph nodes. It is important to achieve an accurate diagnosis to rule out the possibility of cancer involvement. What to do with these drugs is yet to be clarified. It seems reasonable to prioritize cancer treatment so it is not mandatory to stop these drugs.

Quantum-like influence diagrams for decision-making.

This article proposes a novel and comprehensive framework on how to describe the probabilistic nature of decision-making process. We suggest extending the quantum-like Bayesian network formalism to incorporate the notion of maximum expected utility to model human paradoxical, sub-optimal and irrational decisions. What distinguishes this work is that we take advantage of the quantum interference effects produced in quantum-like Bayesian Networks during the inference process to influence the probabilities used to compute the maximum expected utility of some decision. The proposed quantum-like decision model is able to (1) predict the probability distributions found in different experiments reported in the literature by modelling uncertainty through quantum interference, (2) to identify decisions that the decision-makers perceive to be optimal within their belief space, but that are actually irrational with respect to expected utility theory, (3) gain an understanding of how the decision-maker's beliefs evolve within a decision-making scenario. The proposed model has the potential to provide new insights in decision science, as well as having direct implications for decision support systems that deal with human data, such as in the fields of economics, finance, psychology, etc.

Bistable probabilities: a unified framework for studying rationality and irrationality in classical and quantum games.

This article presents a unified probabilistic framework that allows both rational and irrational decision-making to be theoretically investigated and simulated in classical and quantum games. Rational choice theory is a basic component of game-theoretic models, which assumes that a decision-maker chooses the best action according to their preferences. In this article, we define irrationality as a deviation from a rational choice. Bistable probabilities are proposed as a principled and straightforward means for modelling (ir)rational decision-making in games. Bistable variants of classical and quantum Prisoner's Dilemma, Stag Hunt and Chicken are analysed in order to assess the effect of (ir)rationality on agent utility and Nash equilibria. It was found that up to three Nash equilibria exist for all three classical bistable games and maximal utility was attained when agents were rational. Up to three Nash equilibria exist for all three quantum bistable games; however, utility was shown to increase according to higher levels of agent irrationality.