Archivio istituzionale della ricerca - Alma Mater Studiorum Università di Bologna
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Active inference and cognitive control: Balancing deliberation and habits through precision optimization
No full textWe advance a novel formulation of cognitive control within the active inference framework. The theory proposes that cognitive control amounts to optimising a precision parameter, which acts as a control signal and balances the contributions of deliberative and habitual components of action selection. To illustrate the theory, we simulate a driving scenario in which the driver follows a well-known route, but encounters unexpected challenges. Our simulations show that a standard active inference model can form adaptive habits; i.e., can pass from deliberative to habitual control when the context is stable, but generally fails to revert to deliberative control, when the context changes. To address this failure of context-sensitivity, we introduce a novel type of hierarchical active inference, in which a lower level is responsible for behavioural control and the higher (or meta-cognitive) level observes the belief updating of the lower level below and is responsible for cognitive control. Crucially, the meta-cognitive level can both form habits and suspend them, by controlling the (precision) parameter that prioritizes deliberative choices at the behavioural level. Furthermore, we show that several processes linked to cognitive control - such as surprise detection, cognitive conflict monitoring, control signal regulation and specification, the simulation of future outcomes and the assessment of the costs of control and mental effort - stem coherently from the free energy minimization scheme that underpins active inference. Finally, we discuss the putative neurobiology of cognitive control by simulating brain dynamics in the mesolimbic and mesocortical pathways of the dopamine system, the dorsal anterior cingulate cortex and the locus coeruleus
High-grade Endometrial Endometrioid Carcinoma: A Case Report of Complete Transdifferentiation to Pilomatrix-like Carcinoma
No full textIntroduction Endometrial endometrioid carcinomas can show multiple lines of differentiation, including pilomatrix-like high-grade endometrioid carcinoma, a recently described tumor with similarity to cutaneous pilomatrix carcinoma and associated with very aggressive clinical behavior. Methods We present a 56-year-old woman with an endometrial tumor associated with secondary involvement of both ovaries, left tubo-ovarian ligament and obturator lymph nodes. The diagnosis of high-grade endometrioid carcinoma in a previously performed curettage was confirmed in the hysterectomy specimen. Results Microscopically, the tumor exhibited a solid, nested/insular pattern with basaloid cells, predominantly seen at the periphery, ghost cell keratinization towards the center of the nests, and extensive geographic necrosis. No low-grade endometrioid carcinoma component was identified throughout the primary tumor or metastases after extensive sampling. Immunohistochemical assessment showed aberrant cytoplasmic and nuclear expression of beta-catenin, and focal CDX2 expression. Tumor cells were negative for PAX8, and estrogen and progesterone receptors (ER/PR). The next-generation sequencing (NGS) analysis found a CTNNB1 pathogenic mutation (p.Ser37Phe, c.110C > T; variant allele frequency: 18.6%). Based on these morphologic, immunohistochemistry and NGS analysis, a diagnosis of pilomatrix-like high-grade endometrioid carcinoma was established. Conclusion The absence of a low-grade endometrioid carcinoma component makes this pilomatrix-like high-grade endometrioid carcinoma, a very rare tumor, even more special. This and the absence of PAX8 and ER/PR expression in an unusual morphological context proved to be diagnostically challenging. This patient's presentation at high stage is concordant with the literature's description of this tumor as aggressive. It is not yet known whether standard adjuvant therapies for high-risk endometrial carcinomas are effective
Language models learn to represent antigenic properties of human influenza A(H3) virus
No full textGiven that influenza vaccine effectiveness depends on a good antigenic match between the vaccine and circulating viruses, it is important to assess the antigenic properties of newly emerging variants continuously. With the increasing application of real-time pathogen genomic surveillance, a key question is if antigenic properties can reliably be predicted from influenza virus genomic information. Based on validated linked datasets of influenza virus genomic and wet lab experimental results, in silico models may be of use to learn to predict immune escape of variants of interest starting from the protein sequence only. In this study, we compared several machine-learning methods to reconstruct antigenic map coordinates for HA1 protein sequences of influenza A(H3N2) virus, to rank substitutions responsible for major antigenic changes, and to recognize variants with novel antigenic properties that may warrant future vaccine updates. Methods based on deep learning language models (BiLSTM and ProtBERT) and more classical approaches based solely on genetic distances and physicochemical properties of amino acid sequences had comparable performances over the coarser features of the map, but the first two performed better over fine-grained features like single amino acid-driven antigenic change and in silico deep mutational scanning experiments to rank the substitutions with the largest impact on antigenic properties. Given that the best performing model that produces protein embeddings is agnostic to the specific pathogen, the presented approach may be applicable to other pathogens
PPFM: An Object-Oriented C++ Library for Thermodynamic and Transport Properties Calculation
No full textVaginal Lactobacillus gasseri biosurfactant: a novel bio- and eco-compatible anti-Candida agent
No full textVulvovaginal candidiasis (VVC) and recurrent vulvovaginal candidiasis (RVVC), caused by Candida spp. overgrowth, are common and challenging infections of the genital tract. Among Candida virulence factors, the ability to adhere to host epithelium and to form biofilms are frequently retrieved, especially in RVVC. Vaginal pathogen overgrowth is counteracted by resident lactobacilli, which exert a barrier thanks to the production of antimicrobial metabolites, such as biosurfactants (BS).
BS was recovered from vaginal Lactobacillus gasseri BC12 and its chemical characteristics as well as its ability to lower the surface tension and to emulsify two different immiscible phases were investigated. BS showed the typical features of a lipopeptide with a critical micellar concentration of 1.2 mg/mL. BS showed antibiofilm activity towards various Candida albicans and non-albicans isolates, notably, it was able to prevent biofilm formation and eradicate preformed biofilms. The absence of cytotoxicity of BS and its ability to counteract the adhesion of Candida spp. were highlighted on HeLa cells through MTT and competition/exclusion assays, respectively. The environmental impact of BS was also investigated on a microcosm model (spring water) by culture-based and molecular (16S rRNA-targeted Illumina sequencing) methods, and no remarkable modifications in the taxonomy composition of the bacterial ecosystem were observed.
To conclude, BS from L. gasseri BC12 appears as a promising, biocompatible and environmentally friendly approach to prevent and treat VVC/RVVC
Thrombectomy Selection in the Large Core Era: Implications for Regional Transfers
No full textPurpose of ReviewThis review aims to evaluate recent advances in large core stroke management with a focus on diagnostic imaging protocols to select patients for endovascular therapy.Recent FindingsRecent randomized controlled trials have shown that thrombectomy can lead to favorable outcomes in patients with large infarcts, contradicting previous assumptions that thrombectomy was not indicated in such patients due to higher risks and very low benefits.SummaryAlthough mechanical thrombectomy remains the gold standard of medical treatment for large vessel occlusions with demonstrated salvageable brain tissue, analysis of the results of recent randomized trials in patients with large ischemic stroke should help us expand patient selection, optimize timing, and explore different management modalities to improve the outcomes of therapy in these patients
Enhancing bioactive profiles of elderberry juice through yeast fermentation: a pathway to low-sugar functional beverages
No full textIn response to the growing need for functional beverages, this study aimed to harness yeast metabolism to optimize elderberry juice fermentation, targeting sugar reduction and enrichment of bioactive compounds with enhanced functional properties. Initially, ten yeast strains were screened in synthetic medium and elderberry juice for sugar consumption and ethanol production. Five yeasts with distinct metabolic profiles were selected to generate seven binary cultures (pairing high-with low-to-intermediate-performing strains) for juice fermentation at 30 °C for 36 h. Monocultures and binary cultures were comparatively evaluated for sugar utilization, ethanol production, and the modulation of bioactive compounds. The co-culture of Hanseniaspora uvarum and Metschnikowia pulcherrima with Hanseniaspora opuntiae, resulted in a more balanced metabolic profile, achieving high sugar reduction (80–88 %) and modulating ethanol levels (1.4–1.6 %). The same cultures significantly released phenolics (including chlorogenic acid, quercetin, hyperoside, and isoquercetin) with biological activity. Most binary cultures displayed synergistic proteolytic activity, increasing free amino acids and promoting the release of bioactive amino acid derivatives such as gamma-aminobutyric acid, especially when H. opuntiae was paired with H. uvarum and Saccharomyces cerevisiae with H. uvarum. The shaping of volatile organic compounds by S. cerevisiae favoring alcohol and acids production or non-Saccharomyces strains enhancing ester synthesis, further diversified the sensory profile when combined, contributing to aromatic complexity. In conclusion, binary yeast cultures offer an effective way to enrich low-sugar elderberry beverage with bioactive metabolites and appealing flavor. Future research should focus on in vivo validation of bioactivities, product stability, and consumer acceptability to support industrial application
Trends in medication use during the COVID-19 pandemic in Quebec, Canada
No full textThe COVID-19 pandemic has disrupted health and services worldwide. We aimed to describe the changes in medication use during the COVID-19 pandemic in Quebec, Canada. Using a large healthcare database, we created weekly cohorts of all individuals >= 1 year old covered by the public drug plan from January 2016 to March 2022. We calculated the weekly number of prevalent and new users of different medications, including both chronic and short-term medications. We integrated the 2016-2019 weekly numbers in Quasi-Poisson regressions, with each gender and age group fitted separately. From these models, we estimated the weekly proportions of prevalent and new users expected for 2020-2021 and their 99% prediction interval [99% PI]. Results were analyzed using the ratio of the overall weekly proportion of users (observed/expected) across four periods, selected according to the different waves of the pandemic: Period 1: 1st wave (February 2020-August 2020), Period 2: 2nd wave (August 2020-March 2021), Period 3: 3rd and 4th waves (March 2021-December 2021), and Period 4: 5th and 6th waves (December 2021-March 2022). Each cohort included over 3,000,000 individuals (53% female). The proportion of new users of most medications dropped in Period 1, with exceptions like antipsychotics (ratio of adjusted overall weekly proportion observed/expected [99% PI] 1.02 [1.00-1.04]). From Period 2 onwards, the initiation of antidiabetics, lipid-lowering medications and attention deficit hyperactivity disorder (ADHD) medications, among others, exceeded expected trends, but remained below expectations notably for systemic antibiotics (Period 4: 0.71 [0.69-0.72]), nasal/oral corticosteroids (Period 4: 0.69 [0.67-0.70]/Period 4: 0.69 [0.67-0.70]) and medications for obstructive lung diseases (Period 4: 0.69 [0.68-0.71]). While the prevalent use of most chronic medications remained relatively close to expectations, observed immediate and long-term variations in medication use should be considered in studies including pandemic years and anticipated in public health planning in case of future pandemics
Merging theoretical and practical learning through the 6th edition of the UrbanFarm student challenge
No full textSince 2019, the University of Bologna and the Department of Agricultural and Food Sciences have proposed an innovative learning experience with the UrbanFarm Student Challenge. UrbanFarm2024, the sixth installment, combines competition with project-based learning to propel students beyond the conventional classroom environment. The challenge focused on promoting multidisciplinary and international cooperation between students belonging to the University of Bologna Alma Mater Studiorum in Italy (UNIBO) and the Swedish University of Agricultural Sciences (SLU Alnarp). By utilizing project-based learning in a competitive setting, the students were focused on collaborating with one another to create the best proposal to tackle a practical problem. This edition’s task was to design an urban agriculture system for the Trelleborg prison facility in Skåne County, Sweden. The system had to integrate innovative food technologies and uphold the three pillars of sustainability (environmental, social, and economic). The student groups had the freedom to design their proposal with a focus on improving the inmates’ and staff’s mental health, personal well-being, and providing areas for meaningful leisure time for the inmates. The evaluation of the challenge was conducted by experts and UA practitioners from Italy and Sweden to evaluate the ten presented projects. Finally, this paper will discuss the preparation of UrbanFarm2024, the practical activities that led to the project submissions, and the student sentiment regarding their participation in the challenge to give an overview of the entire experience
High-fidelity surrogate-driven h-refined IGA for free vibration analysis of laminated composite annular plates with radial and curved cracks
No full textDuring their service life, structures often develop cracks, which affect their free vibration behavior. This study
focuses on predicting the free vibration response of cracked laminated composite annular plates with helicoidal
layup schemes, considering both radial and circular cracks. The plate is modeled using isogeometric analysis
based on Reddy’s shear deformation theory. To accurately represent the crack, an adaptive h-refinement strategy
is employed within the crack region, with the refinement level determined by a Gaussian process regression (GPR)
surrogate machine learning model. The surrogate model is trained using preliminary free vibration analyses under
varying boundary conditions, crack lengths, layup schemes, and plate geometries. Results indicate that second-
level refinement is sufficient for modeling radial cracks, whereas higher refinement is necessary for complex
circular cracks. The present data-driven approach enhances computational efficiency while ensuring accurate
vibration analysis of cracked composite plates