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Abstract Mapping brain-behaviour associations is paramount to understand and treat psychiatric disorders. Standard approaches involve investigating the association between one brain and one behavioural variable (univariate) or multiple variables against one brain/behaviour feature (‘single’ multivariate). Recently, large multimodal datasets have propelled a new wave of studies that leverage on ‘doubly’ multivariate approaches capable of parsing the multifaceted nature of both brain and behaviour simultaneously. Within this movement, canonical correlation analysis (CCA) and partial least squares (PLS) emerge as the most popular techniques. Both seek to capture shared information between brain and behaviour in the form of latent variables. We provide an overview of these methods, review the literature in psychiatric disorders, and discuss the main challenges from a predictive modelling perspective. We identified 39 studies across four diagnostic groups: attention deficit and hyperactive disorder (ADHD, k = 4, N = 569), autism spectrum disorders (ASD, k = 6, N = 1731), major depressive disorder (MDD, k = 5, N = 938), psychosis spectrum disorders (PSD, k = 13, N = 1150) and one transdiagnostic group (TD, k = 11, N = 5731). Most studies (67%) used CCA and focused on the association between either brain morphology, resting-state functional connectivity or fractional anisotropy against symptoms and/or cognition. There were three main findings. First, most diagnoses shared a link between clinical/cognitive symptoms and two brain measures, namely frontal morphology/brain activity and white matter association fibres (tracts between cortical areas in the same hemisphere). Second, typically less investigated behavioural variables in multivariate models such as physical health (e.g., BMI, drug use) and clinical history (e.g., childhood trauma) were identified as important features. Finally, most studies were at risk of bias due to low sample size/feature ratio and/or in-sample testing only. We highlight the importance of carefully mitigating these sources of bias with an exemplar application of CCA.

Abstract Using smartphone-based ecological momentary assessment, this study investigated an association between natural diversity on mental wellbeing. A sample of 1,998 participants completed 41,448 assessments between April 2018 and September 2023. Environments which included a larger range of natural features, such as trees, plants and birdlife (high natural diversity) were associated with greater mental wellbeing than environments including a smaller range of natural features (low natural diversity). There was evidence of a mediating effect of natural diversity on the association between natural environments and mental wellbeing. These results highlight the importance of policies and practices that support richness of biodiversity for public mental health.

Accumulating evidence links the microbial communities inhabiting the gut to the pathophysiological processes underlying multiple sclerosis (MS). However, most studies on the microbiome in MS are correlative in nature, thus being at risk of confounding and reverse causality. Mendelian randomization (MR) analyses allow the estimation of the causal relationship between a risk factor and an outcome of interest using genetic variants as proxies for environmental exposures. Here, we performed a two-sample MR to assess the causality between the gut microbiome and MS. We extracted genetic instruments from summary statistics from three large genome-wide association studies (GWASs) on the gut microbiome (18,340, 8959, and 7738 subjects). The exposure data were derived from the latest GWAS on MS susceptibility (47,429 patients and 68,374 controls). We pinpointed several microbial strains whose abundance is linked with enhanced MS risk (Actinobacteria class, Bifidobacteriaceae family, Lactobacillus genus) or protection (Prevotella spp., Lachnospiranaceae genus, Negativibacillus genus). The largest risk effect was seen for Ruminococcus Torques (OR, 2.89, 95% C.I. 1.67–5, p = 1.51 × 10−4), while Akkermansia municiphila emerged as strongly protective (OR, 0.43, 95% C.I. 0.32–0.57, p = 1.37 × 10−8). Our findings support a causal relationship between the gut microbiome and MS susceptibility, reinforcing the relevance of the microbiome–gut–brain axis in disease etiology, opening wider perspectives on host–environmental interactions for MS prevention.

Oral melanomas are the most common oral malignancies in dogs and are characterized by an aggressive nature, invasiveness, and poor prognosis. With biological and genetic similarities to human oral melanomas, they serve as a valuable spontaneous comparative model. Primary cell cultures are widely used in human medicine and, more recently, in veterinary medicine to study tumorigenesis, cancer progression, and innovative therapeutic approaches. This study aims to establish two- and three-dimensional primary cell lines from oral canine melanomas using fine-needle aspiration as a minimally invasive sampling method. For this study, samples were collected from six dogs, represented by four primary oral melanomas and five lymph nodal metastases. The cells were digested to obtain single-cell suspensions, seeded in flasks, or processed with Matrigel® to form organoids. The cell cultures were characterized through flow cytometry using antibodies against Melan-A, PNL2, and Sox-10. This technique offers a minimally invasive means to obtain cell samples, particularly beneficial for patients that are ineligible for surgical procedures, and enables the establishment of in vitro models crucial for comparative studies in mucosal melanoma oncology. To the best of our knowledge, this is the first work establishing neoplastic primary cell cultures via fine-needle aspiration in dogs.

Previous exposure to Epstein–Barr virus (EBV) is strongly associated with the development of multiple sclerosis (MS). By contrast, past cytomegalovirus (CMV) infection may have no association, or be negatively associated with MS. This study aimed to investigate the associations of herpesvirus infections with MS in an Italian population. Serum samples (n = 200) from Italian people with multiple sclerosis (PwMS) classified as the relapsing-and-remitting clinical phenotype and (n = 137) healthy controls (HCs) were obtained from the CRESM Biobank, Orbassano, Italy. Both PwMS and HCs samples were selected according to age group (20–39 years, and 40 or more years) and sex. EBV virus capsid antigen (VCA) IgG, EBV nucleic acid-1 antigen (EBNA-1) IgG, CMV IgG, herpes simplex virus (HSV) IgG, and varicella zoster virus (VZV) IgG testing was undertaken using commercial ELISAs. EBV VCA IgG and EBNA-1 IgG seroprevalences were 100% in PwMS and 93.4% and 92.4%, respectively, in HCs. EBV VCA IgG and EBNA-1 IgG levels were higher (p < 0.001) in PwMS compared with HCs. For PwMS, the EBNA-1 IgG levels decreased with age, particularly in females. The CMV IgG seroprevalence was 58.7% in PwMS and 62.9% in HCs. CMV IgG seroprevalence increased with age. The HSV IgG seroprevalence was 71.2% in PwMS and 70.8% in HCs. HSV IgG levels were lower (p = 0.0005) in PwMS compared with HCs. VZV IgG seroprevalence was 97.5% in PwMS and 98.5% in HCs. In the population studied, several herpesvirus infections markers may have been influenced by the age and sex of the groups studied. The lack of a negative association of MS with CMV infection, and the observation of lower levels of HSV IgG in PwMS compared with HCs are findings worthy of further investigation.

In the present article, optimal control problems for linear parabolic partial differential equations (PDEs) with time-dependent coefficient functions are considered. One of the common approach in literature is to derive the first-order sufficient optimality system and to apply a finite element (FE) discretization. This leads to a specific linear but high-dimensional time variant (LTV) dynamical system. To reduce the size of the LTV system, we apply a tailored reduced order modeling technique based on empirical gramians and derived directly from the first-order optimality system. For testing purpose, we focus on two specific examples: a multiobjective optimization and a closed-loop optimal control problem. Our proposed methodology results to be better performing than a standard proper orthogonal decomposition (POD) approach for the above mentioned examples.

Abstract No reliable anatomical or functional alterations have been confirmed in psychiatric neuroimaging; however it can become reliable with translational impact on clinical practice when considering crucial methodological issues. We provide guidelines to authors, editors and reviewers in the implementation/evaluation of neuroimaging studies to bend neuroimaging to be more than basic neuroscience.

Abstract Although the discovery of the critical role of α-synuclein (α-syn) in the pathogenesis of Parkinson’s disease (PD) is now twenty-five years old, it still represents a milestone in PD research. Abnormal forms of α-syn trigger selective and progressive neuronal death through mitochondrial impairment, lysosomal dysfunction, and alteration of calcium homeostasis not only in PD but also in other α-syn-related neurodegenerative disorders such as dementia with Lewy bodies, multiple system atrophy, pure autonomic failure, and REM sleep behavior disorder. Furthermore, α-syn-dependent early synaptic and plastic alterations and the underlying mechanisms preceding overt neurodegeneration have attracted great interest. In particular, the presence of early inflammation in experimental models and PD patients, occurring before deposition and spreading of α-syn, suggests a mechanistic link between inflammation and synaptic dysfunction. The knowledge of these early mechanisms is of seminal importance to support the research on reliable biomarkers to precociously identify the disease and possible disease-modifying therapies targeting α-syn. In this review, we will discuss these critical issues, providing a state of the art of the role of this protein in early PD and other synucleinopathies.

Background: Severe coronavirus disease 2019 (COVID-19) is associated with multiple comorbidities and is characterized by an auto-aggressive inflammatory state leading to massive collateral damage. To identify preventive and therapeutic strategies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), it is important to ascertain the molecular interactions between virus and host, and how they translate into disease pathophysiology. Methods: We matched virus-human protein interactions of human coronaviruses and other respiratory viruses with lists of genes associated with autoimmune diseases and comorbidities associated to worse COVID-19 course. We then selected the genes included in the statistically significant intersection between SARS-CoV-2 network and disease associated gene sets, identifying a meta-interactome. We analyzed the meta-interactome genes expression in samples derived from lungs of infected humans, and their regulation by IFN-β. Finally, we performed a drug repurposing screening to target the network's most critical nodes. Results: We found a significant enrichment of SARS-CoV-2 interactors in immunological pathways and a strong association with autoimmunity and three prognostically relevant conditions (type 2 diabetes, coronary artery diseases, asthma), that present more independent physiopathological subnetworks. We observed a reduced expression of meta-interactome genes in human lungs after SARS-CoV-2 infection, and a regulatory potential of type I interferons. We also underscored multiple repurposable drugs to tailor the therapeutic strategies. Conclusions: Our data underscored a plausible genetic background that may contribute to the distinct observed pathophysiologies of severe COVID-19. Also, these results may help identify the most promising therapeutic targets and treatments for this condition.

Resumo Objetivo Analisar a tendência da mortalidade por suicídio no estado do Espírito Santo e em sua Região Serrana no período de 1996 a 2020. Métodos Estudo descritivo e analítico de série temporal com dados consolidados dos óbitos por suicídio na população acima de 15 anos de idade obtidos no Sistema de Informações sobre Mortalidade. As unidades de análise foram o estado do Espírito Santo e sua Região Serrana. A análise da tendência foi verificada pela regressão de Prais-Winsten e pelo cálculo da variação percentual anual. Resultados Foram notificados 3.922 óbitos por suicídio no Espírito Santo e, destes, 525 na Região Serrana. A tendência da mortalidade por suicídio no estado foi crescente na população geral acima de 15 anos (APC= 5,1; IC95%= 0,28-9,92; p=0,039). A tendência da mortalidade se manteve crescente entre a população feminina, tanto em relação ao estado (APC= 6;5; IC95%= 1,55-14,46; p=0,012) como na região serrana (APC= 15,2; IC95%= 1,21-29,20; p=0,035). A mortalidade foi crescente na faixa etária de 30 a 59 anos no estado (APC= 3,4; IC95%= 0,62-6,10; p=0,018) e na Região Serrana (APC= 2,9; IC95%= 2,02-3,86; p

To date, the studies on managerial loss aversion have produced contradictory findings, making it impossible to: (i) identify the ultimate impact of managerial loss aversion on the value that organisations create for themselves and for their stakeholders, and (ii) mitigate the effect of managerial loss aversion to improve corporate value creation. With the aim of filling this gap, the authors of this paper first performed a Systematic Literature Review (SLR), resulting in 65 relevant papers. The 65 papers were then analysed through a Thematic Analysis (TA), which was aimed at isolating and revising the single effects of managerial loss aversion on the corporate value creation process. Once it became clear when and how managerial loss aversion leads to negative impacts on corporate value creation (such as suboptimal investments in corporate social responsibility, short-term-oriented budget expenditures, illegal corporate conduct in favourable contexts, and low demand for audit quality), a novel theoretical framework was built. This framework proposes some preliminary approaches to mitigate these detrimental effects. In particular, future empirical research may operationalise potential debiasing strategies, derived from critical analysis of the literature, to reduce managerial loss aversion in different business settings, thereby improving corporate value creation.

The present study investigated the clinical utility of ultrasound imaging (USI) for assessing changes in an individual’s quadriceps muscle and subcutaneous fat (SF) thickness of the anterior thigh and their relative proportions. A patient was studied prior to and after anterior cruciate ligament reconstruction (ACLR) surgery and during rehabilitation. This case study involved an 18-year-old female recreational athlete with a complete tear of the anterior cruciate ligament (ACL). Tissue thickness (SF and quadriceps muscle) was measured from transverse USI of the anterior thigh before surgery, at weekly intervals during 12 weeks of postsurgery, and then every 2 weeks for the following 12 weeks (total of 21 measurement sets). Statistically significant differences presurgery to postrehabilitation were found for muscle thickness (p=0.04) and SF tissue thickness (p=0.04) measurements. There was no difference in muscle to fat ratio (p=0.08). Changes in measurements greater than the reported minimal detectable change (MDC) demonstrate the sensitivity of the USI technique as an objective tool to assess clinically useful changes in an individual’s anterior thigh muscle thickness post-ACLR surgery and during rehabilitation.