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Alzheimer’s disease (AD) is a neurodegenerative brain disorder that affects cognitive functioning and memory. Current diagnostic tools, including neuroimaging techniques and cognitive questionnaires, present limitations such as invasiveness, high costs, and subjectivity. In recent years, interest has grown in using electroencephalography (EEG) for AD detection due to its non-invasiveness, low cost, and high temporal resolution. In this regard, this work introduces a novel metric for AD detection by using multiscale fuzzy entropy (MFE) to assess brain complexity, offering clinicians an objective, cost-effective diagnostic tool to aid early intervention and patient care. To this purpose, brain entropy patterns in different frequency bands for 35 healthy subjects (HS) and 35 AD patients were investigated. Then, based on the resulting MFE values, a specific detection algorithm, able to assess brain complexity abnormalities that are typical of AD, was developed and further validated on 24 EEG test recordings. This MFE-based method achieved an accuracy of 83% in differentiating between HS and AD, with a diagnostic odds ratio of 25, and a Matthews correlation coefficient of 0.67, indicating its viability for AD diagnosis. Furthermore, the algorithm showed potential for identifying anomalies in brain complexity when tested on a subject with mild cognitive impairment (MCI), warranting further investigation in future research.

VersaLive is a versatile microfluidic platform with flexible input modes and low-volume media reservoirs that can be used for time-lapse live cell imaging, immunostaining, cell recovery, cell lysis and plasmid transfection.

Abstract Through long-term training, music experts acquire complex and specialized sensorimotor skills, which are paralleled by continuous neuro-anatomical and -functional adaptations. The underlying neuroplasticity mechanisms have been extensively explored in decades of research in music, cognitive, and translational neuroscience. However, the absence of a comprehensive review and quantitative meta-analysis prevents the plethora of variegated findings to ultimately converge into a unified picture of the neuroanatomy of musical expertise. Here, we performed a comprehensive neuroimaging meta-analysis of publications investigating neuro-anatomical and -functional differences between musicians (M) and non-musicians (NM). Eighty-four studies were included in the qualitative synthesis. From these, 58 publications were included in coordinate-based meta-analyses using the anatomic/activation likelihood estimation (ALE) method. This comprehensive approach delivers a coherent cortico-subcortical network encompassing sensorimotor and limbic regions bilaterally. Particularly, M exhibited higher volume/activity in auditory, sensorimotor, interoceptive, and limbic brain areas and lower volume/activity in parietal areas as opposed to NM. Notably, we reveal topographical (dis-)similarities between the identified functional and anatomical networks and characterize their link to various cognitive functions by means of meta-analytic connectivity modelling. Overall, we effectively synthesized decades of research in the field and provide a consistent and controversies-free picture of the neuroanatomy of musical expertise.

When sensory input conveys rhythmic regularity, we can form predictions about the timing of upcoming events. Although rhythm processing capacities differ considerably between individuals, these differences are often obscured by participant- and trial-level data averaging procedures in M/EEG research. Here, we systematically assessed neurophysiological variability displayed by individuals listening to isochronous (1.54 Hz) equitone sequences interspersed with unexpected (amplitude-attenuated) deviant tones. Our approach aimed at revealing time-varying adaptive neural mechanisms for sampling the acoustic environment at multiple timescales. Rhythm tracking analyses confirmed that individuals encode temporal regularities and form temporal expectations, as indicated in delta-band (1.54 Hz) power and its anticipatory phase alignment to expected tone onsets. Zooming into tone- and participant-level data, we further characterized intra- and inter-individual variabilities in phase-alignment across auditory sequences. Further, individual modeling of beta-band tone-locked responses showed that a subset of auditory sequences was sampled rhythmically by superimposing binary (strong-weak; S-w), ternary (S-w-w) and mixed accentuation patterns. In these sequences, neural responses to standard and deviant tones were modulated by a binary accentuation pattern, thus pointing towards a mechanism of dynamic attending. Altogether, the current results point toward complementary roles of delta- and beta-band activity in rhythm processing and further highlight diverse and adaptive mechanisms to track and sample the acoustic environment at multiple timescales, even in the absence of task-specific instructions.

Summary: Background: Nirmatrelvir/ritonavir treatment decreases the hospitalisation rate in immunocompetent patients with COVID-19, but data on efficacy in patients with haematological malignancy are scarce. Here, we describe the outcome of nirmatrelvir/ritonavir treatment in a large cohort of the latter patients. Methods: This is a retrospective cohort study from the multicentre EPICOVIDEHA registry (NCT04733729) on patients with haematological malignancy, who were diagnosed with COVID-19 between January and September 2022. Patients receiving nirmatrelvir/ritonavir were compared to those who did not. A logistic regression was run to determine factors associated with nirmatrelvir/ritonavir administration in our sample. Mortality between treatment groups was assessed with Kaplan–Meier survival plots after matching all the patients with a propensity score. Additionally, a Cox regression was modelled to detect factors associated with mortality in patients receiving nirmatrelvir/ritonavir. Findings: A total of 1859 patients were analysed, 117 (6%) were treated with nirmatrelvir/ritonavir, 1742 (94%) were treated otherwise. Of 117 patients receiving nirmatrelvir/ritonavir, 80% had received ≥1 anti-SARS-CoV-2 vaccine dose before COVID-19 onset, 13% of which received a 2nd vaccine booster. 5% were admitted to ICU. Nirmatrelvir/ritonavir treatment was associated with the presence of extrapulmonary symptoms at COVID-19 onset, for example anosmia, fever, rhinitis, or sinusitis (aOR 2.509, 95%CI 1.448–4.347) and 2nd vaccine booster (aOR 3.624, 95%CI 1.619–8.109). Chronic pulmonary disease (aOR 0.261, 95%CI 0.093–0.732) and obesity (aOR 0.105, 95%CI 0.014–0.776) were not associated with nirmatrelvir/ritonavir use. After propensity score matching, day-30 mortality rate in patients treated with nirmatrelvir/ritonavir was 2%, significantly lower than in patients with SARS-CoV-2 directed treatment other than nirmatrelvir/ritonavir (11%, p = 0.036). No factor was observed explaining the mortality difference in patients after nirmatrelvir/ritonavir administration. Interpretation: Haematological malignancy patients were more likely to receive nirmatrelvir/ritonavir when reporting extrapulmonary symptoms or 2nd vaccine booster at COVID-19 onset, as opposed to chronic pulmonary disease and obesity. The mortality rate in patients treated with nirmatrelvir/ritonavir was lower than in patients with targeted drugs other than nirmatrelvir/ritonavir. Funding: EPICOVIDEHA has received funds from Optics COMMIT (COVID-19 Unmet Medical Needs and Associated Research Extension) COVID-19 RFP program by GILEAD Science, United States (Project 2020-8223).

Introduction: The ongoing emergence of SARS-CoV-2 variants poses significant challenges to existing therapeutics. The spike (S) glycoprotein is central to both viral entry and cell-to-cell transmission via syncytia formation, a process that confers resistance to neutralizing antibodies. The mechanisms underlying this resistance, particularly in relation to spike-mediated fusion, remain poorly understood. Methods: We analyzed two clinical SARS-CoV-2 isolates differing by a single amino acid substitution in the S protein. Using biochemical and cell-based assays, we evaluated entry kinetics, syncytia formation, and the neutralizing efficacy of convalescent sera. These parameters were further correlated with S-mediated cell-cell fusion activity. Results: The single amino acid substitution significantly altered entry kinetics and enhanced syncytia formation. This modification did not diminished the neutralizing capacity of convalescent sera, but it increased the efficiency of S-induced cell-cell fusion. These findings highlight the mutation's impact on viral transmissibility and immune evasion. Discussion: Our study demonstrates that even minor changes in the S protein can profoundly influence SARS-CoV-2 transmissibility and resistance to antibody-mediated neutralization. Understanding the molecular basis of S-mediated cell-cell fusion is crucial for anticipating the impact of emerging variants and developing next-generation therapeutic strategies. These insights provide a framework for predicting variant fitness and optimizing treatment approaches against future SARS-CoV-2 variants. [ABSTRACT FROM AUTHOR]

This study investigates the effectiveness of amplitude transformation in enhancing the performance and robustness of Multiscale Fuzzy Entropy for Alzheimer's disease detection using electroencephalography signals. Multiscale Fuzzy Entropy is a complexity measure particularly sensitive to intra- and inter-subject variations in signal amplitude, as well as the selection of key parameters such as embedding dimension (m) and similarity criterion (r), which often result in inconsistent outcomes when applied to multivariate data, such as electroencephalography signals. To address these challenges and to generalize the possibility of adopting Multiscale Fuzzy Entropy as a diagnostic tool for Alzheimer's disease, this research explores amplitude transformation preprocessing on electroencephalography signals in Multiscale Fuzzy Entropy calculation across varying parameters. The statistical analysis of the obtained results demonstrates that amplitude transformation preprocessing significantly enhances Multiscale Fuzzy Entropy's ability to detect Alzheimer's disease, achieving higher and more consistent significant comparison percentages, with an average of 73.2% across all parameter combinations, compared with only one raw data combination exceeding 65%. Clustering analysis corroborates these findings, showing that amplitude transformation improves the differentiation between Alzheimer's disease patients and healthy subjects. These results highlight the potential of amplitude transformation to stabilize Multiscale Fuzzy Entropy performance, making it a more reliable tool for early Alzheimer's disease detection. [ABSTRACT FROM AUTHOR]

Purpose Acquisition and validation methods Data format and usage notes Potential applications Evaluating deformable image registration (DIR) algorithms is vital for enhancing algorithm performance and gaining clinical acceptance. However, there is a notable lack of dependable DIR benchmark datasets for assessing DIR performance except for lung images. To address this gap, we aim to introduce our comprehensive liver computed tomography (CT) DIR landmark dataset library. This dataset is designed for efficient and quantitative evaluation of various DIR methods for liver CTs, paving the way for more accurate and reliable image registration techniques.Forty CT liver image pairs were acquired from several publicly available image archives and authors’ institutions under institutional review board (IRB) approval. The images were processed with a semi‐automatic procedure to generate landmark pairs: (1) for each case, liver vessels were automatically segmented on one image; (2) landmarks were automatically detected at vessel bifurcations; (3) corresponding landmarks in the second image were placed using two deformable image registration methods to avoid algorithm‐specific biases; (4) a comprehensive validation process based on quantitative evaluation and manual assessment was applied to reject outliers and ensure the landmarks’ positional accuracy. This workflow resulted in an average of ∼56 landmark pairs per image pair, comprising a total of 2220 landmarks for 40 cases. The general landmarking accuracy of this procedure was evaluated using digital phantoms and manual landmark placement. The landmark pair target registration errors (TRE) on digital phantoms were 0.37 ± 0.26 and 0.55 ± 0.34 mm respectively for the two selected DIR algorithms used in our workflow, with 97% of landmark pairs having TREs below 1.5 mm. The distances from the calculated landmarks to the averaged manual placement were 1.27 ± 0.79 mm.All data, including image files and landmark information, are publicly available at Zenodo (https://zenodo.org/records/13738577). Instructions for using our data can be found on our GitHub page at https://github.com/deshanyang/Liver‐DIR‐QA.The landmark dataset generated in this work is the first collection of large‐scale liver CT DIR landmarks prepared on real patient images. This dataset can provide researchers with a dense set of ground truth benchmarks for the quantitative evaluation of DIR algorithms within the liver. [ABSTRACT FROM AUTHOR]

Objective: The aims of this study were to provide population-based estimates of prevalence and incidence of any dementia and Alzheimer's dementia (AD) in the Campania region (South Italy) and to validate towards a clinical registry. Methods: This was a population-based study, using routinely collected healthcare data of individuals living in the Campania region (South Italy) from 2015 to 2020. We included individuals aged ≥65 years alive at the prevalence day (January 1, 2021) who had at least one administrative record for dementia and/or AD from 2015 to 2020. Age-and sex-standardised prevalence rates were calculated using direct standardisation method (European population in 2020 as the reference population). To estimate the incidence, we tested three possible algorithms, which differed for the duration of the time interval between study baseline (January 1, 2015) and index date (first record for dementia and/or AD in administrative databases). We employed a clinical database for the validation of our algorithms towards neuropsychological test results. Results: Among individuals aged over 65 years, 80,392 had dementia, of which 35,748 had AD. The age- and sex-standardised prevalence rates per 1,000 individuals for any dementia and AD were 77.64 (95% confidence interval [CI] = 77.57; 77.68) and 34.05 (95% CI = 34.01; 34.09), respectively. There were 82.10 incident cases of any dementia per 100,000 per year (0.79 sensitivity and 0.62 specificity) and 59.89 incident cases of AD per 100,000 per year (0.80 sensitivity and 0.59 specificity). The capture-recapture method showed a very low number of undetected cases (1.7% for any dementia and 3.0% for AD). Our algorithms showed acceptable performance with the area under the curve ranging from 0.59 to 0.72 and a double likelihood ratio of correctly identifying individuals above and below mini-mental status examination (MMSE) standard cut-offs (24 and 26). Conclusions: Prevalence and incidence of any dementia and AD in the Campania region (South Italy) from 2015 to 2020 are in line with previous estimates from other countries. Our algorithm, integrating administrative and clinical data, holds potential for assessing dementia's epidemiological burden, identifying risk factors, planning healthcare access, and developing prevention strategies. Plain Language Summary: Dementia is a loss of memory and other functions related to thinking and to the ability to do everyday chores, usually occurring in the elderly and getting worse over time. The most common kind is Alzheimer's dementia. Here, we estimated the number of people who are sick with dementia (prevalence) and how many new cases of dementia there are (incidence) in the Campania region (South Italy) from 2015 to 2020. We included individuals aged 65 years and above who have used dementia medications, were admitted to hospitals due to dementia, and/or had payment exemptions for dementia. Among 1,118,545 individuals older than 65 years living in the Campania region of Italy (among 5,624,260 inhabitants), we identified 80,392 people older than 65 years with dementia (62.4% females; age about 80 years), among which 35,748 people had Alzheimer's dementia (63.0% females; age about 79 years). Based on these numbers, we estimated 77 people living with dementia per 1,000 people (85 for females and 67 for males) and 34 with Alzheimer's dementia per 1,000 people (37 for females and 29 for males). The number of new cases per year was 82 per 100,000 for any dementia and 59 for Alzheimer's dementia. We showed that our data were accurate by comparing results of tests measuring memory and other functions and found that only 1.7–3.0% of cases remained undetected. These measures will be important to identify risk factors, guide prevention strategies, and improve care and support for affected individuals and their families. [ABSTRACT FROM AUTHOR]

The cannabinoid receptor 1 (CB1R) plays a pivotal role in regulating various physiopathological processes, thus positioning itself as a promising and sought-after therapeutic target. However, the search for specific and effective CB1R ligands has been challenging, prompting the exploration of drug repurposing (DR) strategies. In this study, we present an innovative DR approach that combines computational screening and experimental validation to identify potential Food and Drug Administration (FDA)-approved compounds that can interact with the CB1R. Initially, a large-scale virtual screening was conducted using molecular docking simulations, where a library of FDA-approved drugs was screened against the CB1R’s three-dimensional structures. This in silico analysis allowed us to prioritize compounds based on their binding affinity through two different filters. Subsequently, the shortlisted compounds were subjected to in vitro assays using cellular and biochemical models to validate their interaction with the CB1R and determine their functional impact. Our results reveal FDA-approved compounds that exhibit promising interactions with the CB1R. These findings open up exciting opportunities for DR in various disorders where CB1R signaling is implicated. In conclusion, our integrated computational and experimental approach demonstrates the feasibility of DR for discovering CB1R modulators from existing FDA-approved compounds. By leveraging the wealth of existing pharmacological data, this strategy accelerates the identification of potential therapeutics while reducing development costs and timelines. The findings from this study hold the potential to advance novel treatments for a range of CB1R -associated diseases, presenting a significant step forward in drug discovery research.

O artigo tem como objetivo analisar três representações acerca da classe trabalhadora brasileira, presentes em Direito do Trabalho e Democracia Social, coletânea de textos de autoria de Oliveira Vianna, e interpelá-las como artifícios funcionais ao processo de justificação de um modelo de regulação jurídica do trabalho ideologicamente associado ao aprofundamento do autoritarismo e do capitalismo no Brasil. Para isso, analisa a recepção das representações de um povo pacífico, insolidário e avesso à luta de classes na revista Cultura Política (1941-1943), interpelando como as descrições são articuladas normativamente e demarcam ideias-forças operacionalizadas na institucionalidade do campo jurídico trabalhista brasileiro, inclusive em sua atualidade.

Human Immunodeficiency Virus (HIV) is still one of the major global health issues, and despite significant efforts that have been put into studying the pathogenesis of HIV infection, several aspects need to be clarified, including how innate immunity acts in different anatomical compartments. Given the nature of HIV as a sexually transmitted disease, one of the aspects that demands particular attention is the mucosal innate immune response. Given this scenario, we focused our attention on the interplay between HIV and mucosal innate response: the different mucosae act as a physical barrier, whose integrity can be compromised by the infection, and the virus-cell interaction induces the innate immune response. In addition, we explored the role of the mucosal microbiota in facilitating or preventing HIV infection and highlighted how its changes could influence the development of several opportunistic infections. Although recent progress, a proper characterization of mucosal innate immune response and microbiota is still missing, and further studies are needed to understand how they can be helpful for the formulation of an effective vaccine.

Mucorales are ubiquitous environmental molds responsible for mucormycosis in diabetic, immunocompromised, and severely burned patients. Small outbreaks of invasive wound mucormycosis (IWM) have already been reported in burn units without extensive microbiological investigations. We faced an outbreak of IWM in our center and investigated the clinical isolates with whole-genome sequencing (WGS) analysis. We analyzed M. circinelloides isolates from patients in our burn unit (BU1, Hôpital Saint-Louis, Paris, France) together with nonoutbreak isolates from Burn Unit 2 (BU2, Paris area) and from France over a 2-year period (2013 to 2015). A total of 21 isolates, including 14 isolates from six BU1 patients, were analyzed by whole-genome sequencing (WGS). Phylogenetic classification based on de novo assembly and assembly free approaches showed that the clinical isolates clustered in four highly divergent clades. Clade 1 contained at least one of the strains from the six epidemiologically linked BU1 patients. The clinical isolates were specific to each patient. Two patients were infected with more than two strains from different clades, suggesting that an environmental reservoir of clonally unrelated isolates was the source of contamination. Only two patients from BU1 shared one strain, which could correspond to direct transmission or contamination with the same environmental source. In conclusion, WGS of several isolates per patients coupled with precise epidemiological data revealed a complex situation combining potential cross-transmission between patients and multiple contaminations with a heterogeneous pool of strains from a cryptic environmental reservoir.IMPORTANCE Invasive wound mucormycosis (IWM) is a severe infection due to environmental molds belonging to the order Mucorales. Severely burned patients are particularly at risk for IWM. Here, we used whole-genome sequencing (WGS) analysis to resolve an outbreak of IWM due to Mucor circinelloides that occurred in our hospital (BU1). We sequenced 21 clinical isolates, including 14 from BU1 and 7 unrelated isolates, and compared them to the reference genome (1006PhL). This analysis revealed that the outbreak was mainly due to multiple strains that seemed patient specific, suggesting that the patients were more likely infected from a pool of diverse strains from the environment rather than from direct transmission among them. This study revealed the complexity of a Mucorales outbreak in the settings of IWM in burn patients, which has been highlighted based on WGS combined with careful sampling.