Editorial: Can't get you out of my head: brain-body interactions in perseverative cognition

Perseverative cognition represents a prototypical example of how our internal thoughts can impact our psychological and physical health, as if we were facing an actual environmental stressor (Brosschot et al., 2006). The mechanisms involved—together with other emblematic examples like the placebo effect—provide clear evidence for brain-body interaction. This collection of articles presents recent advances in our understanding of perseverative cognition that have arisen from the integration of multidisciplinary approaches encompassing cognitive and clinical psychology, affective neuroscience, and autonomic physiology. These advances carry with them the promise of more effective treatments to mitigate the negative consequences of maladaptive perseverative cognition on health and well-being

Algorithmic iteration for computational intelligence

Machine awareness is a disputed research topic, in some circles considered a crucial step in realising Artificial General Intelligence. Understanding what that is, under which conditions such feature could arise and how it can be controlled is still a matter of speculation. A more concrete object of theoretical analysis is algorithmic iteration for computational intelligence, intended as the theoretical and practical ability of algorithms to design other algorithms for actions aimed at solving well-specified tasks. We know this ability is already shown by current AIs, and understanding its limits is an essential step in qualifying claims about machine awareness and Super-AI. We propose a formal translation of algorithmic iteration in a fragment of modal logic, formulate principles of transparency and faithfulness across human and machine intelligence, and consider the relevance to theoretical research on (Super)-AI as well as the practical import of our results

Molecularly Imprinted Polymer Micro- and Nano-Particles. A review

In recent years, molecularly imprinted polymers (MIPs) have become an excellent solution to the selective and sensitive determination of target molecules in complex matrices where other similar and relative structural compounds could coexist. Although MIPs show the inherent properties of the polymers, including stability, robustness, and easy/cheap synthesis, some of their characteristics can be enhanced, or new functionalities can be obtained when nanoparticles are incorporated in their polymeric structure. The great variety of nanoparticles available significantly increase the possibility of finding the adequate design of nanostructured MIP for each analytical problem. Moreover, different structures (i.e., monolithic solids or MIPs micro/nanoparticles) can be produced depending on the used synthesis approach. This review aims to summarize and describe the most recent and innovative strategies since 2015, based on the combination of MIPs with nanoparticles. The role of the nanoparticles in the polymerization, as well as in the imprinting and adsorption efficiency, is also discussed through the review

Multiparameter quantum critical metrology

Single parameter estimation is known to benefit from extreme sensitivity to parameter changes in quantum critical systems. However, the simultaneous estimation of multiple parameters is generally limited due to the incompatibility arising from the quantum nature of the underlying system. A key question is whether quantum criticality may also play a positive role in reducing the incompatibility in the simultaneous estimation of multiple parameters. We argue that this is generally the case and verify this prediction in paradigmatic quantum many-body systems close to first and second order phase transitions. The antiferromagnetic and ferromagnetic 1-D Ising chain with both transverse and longitudinal fields are analysed across different regimes and close to criticality

On the machine learning-assisted identification of the fundamental parameters of nonstandard microfin arrays to assess their heat transfer performance

Microfin design for industrial applications has been extensively studied in the past, but the use of innovative techniques that can reveal hitherto unfamiliar morphologies realizable with novel additive manufacturing techniques has not yet been fully exploited. Here, an attempt is made to develop a structured methodology for the assessment of various randomly generated geometries, with the purpose of identifying the most significant geometrical parameters for their thermohydraulic performance. To do so, a computational fluid dynamics (CFD) database consisting of nearly 16,000 geometrical configurations was used, and various feature extraction algorithms were analyzed and compared from a classical, mechanistic perspective, within a structured framework called data interconnectivity and correlation for explainability, or DICE for short. The input parametric search space of geometries is composed of 15 features that represent the coordinates of the vertices of the microfin and the periodic separation between them. Based on data-driven models trained with heat flux and total drag as separate targets, a reduction to just three crucial geometrical parameters is achieved. The physical reasons behind this reduced set of key parameters are discussed. In addition, based on gene expression programming, two mathematical expressions were produced that, with only six of the inputs, are able to model the performance of the parameterized microfin array with a relative error of 13.82% for the heat flux and 3.40% for the total drag. Ultimately, this study successfully addresses the challenge of managing complex, high-dimensional feature spaces through a comprehensive analysis of explainability.Universidade de VigoUniversidade de Vigo/CISU

On malfunctioning software

Artefacts do not always do what they are supposed to, due to a variety of reasons, including manufacturing problems, poor maintenance, and normal wear-and-tear. Since software is an artefact, it should be subject to malfunctioning in the same sense in which other artefacts can malfunction. Yet, whether software is on a par with other artefacts when it comes to malfunctioning crucially depends on the abstraction used in the analysis. We distinguish between “negative” and “positive” notions of malfunction. A negative malfunction, or dysfunction, occurs when an artefact token either does not (sometimes) or cannot (ever) do what it is supposed to. A positive malfunction, or misfunction, occurs when an artefact token may do what is supposed to but, at least occasionally, it also yields some unintended and undesirable effects. We argue that software, understood as type, may misfunction in some limited sense, but cannot dysfunction. Accordingly, one should distinguish software from other technical artefacts, in view of their design that makes dysfunction impossible for the former, while possible for the latter

Carbidopa Alters Tryptophan Metabolism in Breast Cancer and Melanoma Cells Leading to the Formation of Indole-3-Acetonitrile, a Pro-Proliferative Metabolite

Carbidopa is used for the treatment of Parkinson's disease (PD) as an inhibitor of DOPA decarboxylase, and PD patients taking carbidopa have a lower incidence of various tumors, except for breast cancer and melanoma. Recently, it was shown that carbidopa inhibits tryptophan-2,3-dioxygenase (TDO) and kynureninase enzymes. In the present study, the effect of carbidopa on the viability and metabolic profile of breast cancer MCF-7 and melanoma A375 cells was investigated. Carbidopa was not effective in inhibiting MCF-7 and A375 proliferation. Liquid chromatography and mass spectrometry revealed a new compound, identified as indole-3-acetonitrile (IAN), which promoted a concentration-dependent increase in the viability of both cell lines. The results suggest that treatment with carbidopa may alter tryptophan (Trp) metabolism in breast cancer and melanoma leading to the formation of a pro-proliferative Trp metabolite, which may contribute to its failure in reducing breast cancers and melanoma incidence in PD patients taking carbidopa.This work was financed by FEDER—Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020—Operational Programme for Competitiveness and Internationalisation (POCI), Portugal 2020, and by Portuguese funds through FCT, in the framework of the project “Institute for Research and Innovation in Health Sciences” (POCI-01-0145-FEDER-007274).” NV thanks FCT for IF position, Fundação Manuel António da Mota (FMAM, Portugal) for support. The contents of this report are solely the responsibility of the authors and do not necessarily represent the official views of the FCT and FMAMinfo:eu-repo/semantics/publishedVersio

The Left Ventricular Dysfunction Questionnaire: Italian translation and validation.

Patients affected by heart failure have a compromised quality of life (QOL) and in the last few years "health related quality of life" has become an important outcome indicator for the evaluation of heart failure treatment. Methods: Translation into Italian of the Left Ventricular Dysfunction Questionnaire (LVD-36), a new, 36-item, disease-specific health status instrument for patients with congestive heart failure, and its subsequent validation by administration to 50 consecutive patients in our heart failure outpatient clinic. The Italian LVD-36 was compared to the "The Minnesota Living with Heart Failure Questionnaire" (MLHF). Results: The Italian version of the LVD-36 correlates well with MLHF for ejection fraction (EF), NYHA class I and II, etiology and therapy. Since, however, the LVD-36 has only one domain, it may be able to offer more synthetic information than MLHF about patients' status. Conclusions: The Italian version of the LVD-36 appears to be a reliable instrument for assessing patients' QOL and the degree of limitations imposed on them by the disease. It is short, clear and easy to complete. In patients with heart failure the LVD-36 correlates well with the MLHF and may be considered a new disease- specific instrument to estimate changes in health status, and an useful support in optimizing therapeutic options