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Abstract Filial imprinting, a crucial ethological paradigm, provides insights into the neurobiology of early learning and its long-term impact on behaviour. To date, invasive techniques like autoradiography or lesions have been used to study it, limiting the exploration of whole brain networks. Recent advances in fMRI for avian brains now open new windows to explore bird’s brain functions at the network level. We developed an fMRI technique for awake, newly hatched chicks, capturing BOLD signal changes during imprinting experiments. While early memory acquisition phases are understood, long-term storage and retrieval remain unclear. Our findings identified potential long-term storage of imprinting memories across a neural network, including the hippocampal formation, the medial striatum, the arcopallium, and the prefrontal-like nidopallium caudolaterale. This paradigm opens up new avenues for exploring the broader landscape of learning and memory in neonatal vertebrates, enhancing our understanding of behaviour and brain networks.

Abstract Perennial grains, which remain productive for multiple years, rather than growing for only one season before harvest, have deep, dense root systems that can support a richness of beneficial microorganisms, which are mostly underexplored. In this work we isolated forty-three bacterial strains associated with the rhizosphere of the OK72 perennial wheat line, developed from a cross between winter common wheat and Thinopyrum ponticum. Identified using 16S rDNA sequencing, these bacteria were assessed for plant growth-promoting traits such as indole-3-acetic acid, siderophores and ACC-deaminase acid production, biofilm formation, and the ability to solubilize phosphate and proteins. Twenty-five strains exhibiting in vitro significant plant growth promoting traits, belong to wheat keystone genera Pseudomonas, Microbacterium, Variovorax, Pedobacter, Dyadobacter, Plantibacter, and Flavobacterium. Seven strains, including Aeromicrobium and Okibacterium genera, were able to promote root growth in a commercial annual wheat cultivar while strains from Pseudomonas genus inhibited the growth of Aspergillus flavus and Fusarium species, using direct antagonism assays. The same strains produced a high amount of 1-undecanol a volatile organic compound, which may aid in suppressing fungal growth. The study highlights the potential of these bacteria to form new commercial consortia, enhancing the health and productivity of annual wheat crops within sustainable agricultural practices.

Abstract Evolutionarily relevant networks have been previously described in several mammalian species using time-averaged analyses of fMRI time-series. However, fMRI network activity is highly dynamic and continually evolves over timescales of seconds. Whether the dynamic organization of resting-state fMRI network activity is conserved across mammalian species remains unclear. Using frame-wise clustering of fMRI time-series, we find that intrinsic fMRI network dynamics in awake male macaques and humans is characterized by recurrent transitions between a set of 4 dominant, neuroanatomically homologous fMRI coactivation modes (C-modes), three of which are also plausibly represented in the male rodent brain. Importantly, in all species C-modes exhibit species-invariant dynamic features, including preferred occurrence at specific phases of fMRI global signal fluctuations, and a state transition structure compatible with infraslow coupled oscillator dynamics. Moreover, dominant C-mode occurrence reconstitutes the static organization of the fMRI connectome in all species, and is predictive of ranking of corresponding fMRI connectivity gradients. These results reveal a set of species-invariant principles underlying the dynamic organization of fMRI networks in mammalian species, and offer novel opportunities to relate fMRI network findings across the phylogenetic tree.

Abstract Introduction The usual interstitial pneumonia (UIP) pattern, hallmark of idiopathic pulmonary fibrosis (IPF), may induce harmful local overdistension during mechanical ventilation given the juxtaposition of different tissue elasticities. Mechanotransduction, linking mechanical stress and strain to molecular pro-fibrotic pathways, likely contributes to fibrosis progression. Understanding the mechanical forces and aeration patterns in the lungs of IPF patients is crucial for unraveling potential mechanisms of disease progression. Quantitative lung computed tomography (CT) can accurately assess the air content of lung regions, thus informing on zonal distension. This study aims to investigate radiological evidence of lung over aeration in spontaneously breathing UIP patients compared to healthy controls during maximal inspiration. Methods Patients with IPF diagnosis referred to the Center for Rare Lung Diseases of the University Hospital of Modena (Italy) in the period 2020–2023 who underwent High Resolution Computed Tomography (HRCT) scans at residual volume (RV) and total lung capacity (TLC) using standardized protocols were retrospectively considered eligible. Patients with no signs of lung disease at HRCT performed with the same image acquisition protocol nor at pulmonary function test (PFTs) served as controls. Lung segmentation and quantitative analysis were performed using 3D Slicer software. Lung volumes were measured, and specific density thresholds defined over aerated and fibrotic regions. Comparison between over aerated lung at RV and TLC in the two groups and according to lung lobes was sought. Further, the correlation between aerated lung and the extent of fibrosis was assessed and compared at RV and TLC. Results IPF patients (N = 20) exhibited higher over aerated lung proportions than controls (N = 15) both at RV and TLC (4.5% vs. 0.7%, p

Abstract Background Women who have migrated often encounter difficulties in accessing healthcare and experience inequitable sexual and reproductive health outcomes in destination countries. These health inequities include contraceptive access and use. To better understand what influences contraceptive access and use, this scoping review set out to synthesize the evidence on contraceptive access and use and on associated interventions among women with migratory experience in high-income countries (HICs) in Europe, North America and Australasia. Methods The scientific databases PubMed, Web of Science and CINAHL were searched for peer-reviewed quantitative, qualitative and mixed method articles published between January 2000 and June 2023. Articles were included if they reported on studies exploring contraceptive use to prevent pregnancies among women of reproductive age with migratory experience living in HICs. Two researchers independently screened and extracted data from the articles. Findings were categorized by patient and health system level factors according to Levesque et al.’s framework of access to health care. Results A total of 68 articles were included, about half (n = 32) from North America. The articles focused on the individual level rather than the health system level, including aspects such as women’s contraceptive knowledge, the influence of culture and religion on accessing and using contraception, partner involvement, and differing health insurance coverage. On the health system level, the articles highlighted lack of information on contraceptive services, cultural (in)adequacy of services and communication aspects, contraceptives’ side effects, as well as geographic availability and cost of services. The review further identified three articles reporting on interventions related to contraceptive counselling. Conclusions There is a lack of knowledge regarding how health systems impose obstacles to contraceptive services for women with migratory experience on an organizational level, as research has focused heavily on the individual level. This review’s findings may serve as a foundation for further research and advances in policy and practice, specifically recommending early provision of health system related information and contraceptive education, engagement of male partners in contraceptive discourses, cultural competency training for healthcare professionals, and strengthening of interpretation services for contraceptive counselling.

Abstract Bioelectronic therapies modulating the vagus nerve are promising for cardiovascular, inflammatory, and mental disorders. Clinical applications are however limited by side-effects such as breathing obstruction and headache caused by non-specific stimulation. To design selective and functional stimulation, we engineered VaStim, a realistic and efficient in-silico model. We developed a protocol to personalize VaStim in-vivo using simple muscle responses, successfully reproducing experimental observations, by combining models with trials conducted on five pigs. Through optimized algorithms, VaStim simulated the complete fiber population in minutes, including often omitted unmyelinated fibers which constitute 80% of the nerve. The model suggested that all Aα-fibers across the nerve affect laryngeal muscle, while heart rate changes were caused by B-efferents in specific fascicles. It predicted that tripolar paradigms could reduce laryngeal activity by 70% compared to typically used protocols. VaStim may serve as a model for developing neuromodulation therapies by maximizing efficacy and specificity, reducing animal experimentation.

Abstract The macroscale connectome is the network of physical, white-matter tracts between brain areas. The connections are generally weighted and their values interpreted as measures of communication efficacy. In most applications, weights are either assigned based on imaging features–e.g. diffusion parameters–or inferred using statistical models. In reality, the ground-truth weights are unknown, motivating the exploration of alternative edge weighting schemes. Here, we explore a multi-modal, regression-based model that endows reconstructed fiber tracts with directed and signed weights. We find that the model fits observed data well, outperforming a suite of null models. The estimated weights are subject-specific and highly reliable, even when fit using relatively few training samples, and the networks maintain a number of desirable features. In summary, we offer a simple framework for weighting connectome data, demonstrating both its ease of implementation while benchmarking its utility for typical connectome analyses, including graph theoretic modeling and brain-behavior associations.

Abstract Patients with acute exacerbation of lung fibrosis with usual interstitial pneumonia (EUIP) pattern are at increased risk for ventilator-induced lung injury (VILI) and mortality when exposed to mechanical ventilation (MV). Yet, lack of a mechanical model describing UIP-lung deformation during MV represents a research gap. Aim of this study was to develop a constitutive mathematical model for UIP-lung deformation during lung protective MV based on the stress–strain behavior and the specific elastance of patients with EUIP as compared to that of acute respiratory distress syndrome (ARDS) and healthy lung. Partitioned lung and chest wall mechanics were assessed for patients with EUIP and primary ARDS (1:1 matched based on body mass index and PaO2/FiO2 ratio) during a PEEP trial performed within 24 h from intubation. Patient’s stress–strain curve and the lung specific elastance were computed and compared with those of healthy lungs, derived from literature. Respiratory mechanics were used to fit a novel mathematical model of the lung describing mechanical-inflation-induced lung parenchyma deformation, differentiating the contributions of elastin and collagen, the main components of lung extracellular matrix. Five patients with EUIP and 5 matched with primary ARDS were included and analyzed. Global strain was not different at low PEEP between the groups. Overall specific elastance was significantly higher in EUIP as compared to ARDS (28.9 [22.8–33.2] cmH2O versus 11.4 [10.3–14.6] cmH2O, respectively). Compared to ARDS and healthy lung, the stress/strain curve of EUIP showed a steeper increase, crossing the VILI threshold stress risk for strain values greater than 0.55. The contribution of elastin was prevalent at lower strains, while the contribution of collagen was prevalent at large strains. The stress/strain curve for collagen showed an upward shift passing from ARDS and healthy lungs to EUIP lungs. During MV, patients with EUIP showed different respiratory mechanics, stress–strain curve and specific elastance as compared to ARDS patients and healthy subjects and may experience VILI even when protective MV is applied. According to our mathematical model of lung deformation during mechanical inflation, the elastic response of UIP-lung is peculiar and different from ARDS. Our data suggest that patients with EUIP experience VILI with ventilatory setting that are lung-protective for patients with ARDS.

Este artigo se debruça sobre a relação entre História e trama que entra em cena na série Mad Men (Matthew Weiner, AMC, 2007-15) a partir de referências culturais e históricas da década de 1960, período em que se passa sua diegese. Inicialmente investigando como o período histórico é temporalmente estruturado ao longo das temporadas da série, irei posteriormente analisar os usos de músicas de época em seus episódios, destacando como a série quer se posicionar frente à memória cultural daquela década, trabalhar com ela e se legitimar por meio daquilo que cita em cena. Por fim, essa análise permitirá interpretar melhor o projeto crítico de Mad Men e a forma como a série opera uma visão nostálgica sobre o passado.

The Scenario Modeling Hub (SMH) initiative provides projections of potential epidemic scenarios in the United States (US) by using a multi-model approach. Our contribution to the SMH is generated by a multiscale model that combines the global epidemic metapopulation modeling approach (GLEAM) with a local epidemic and mobility model of the US (LEAM-US), first introduced here. The LEAM-US model consists of 3142 subpopulations each representing a single county across the 50 US states and the District of Columbia, enabling us to project state and national trajectories of COVID-19 cases, hospitalizations, and deaths under different epidemic scenarios. The model is age-structured, and multi-strain. It integrates data on vaccine administration, human mobility, and non-pharmaceutical interventions. The model contributed to all 17 rounds of the SMH, and allows for the mechanistic characterization of the spatio-temporal heterogeneities observed during the COVID-19 pandemic. Here we describe the mathematical and computational structure of our model, and present the results concerning the emergence of the SARS-CoV-2 Alpha variant (lineage designation B.1.1.7) as a case study. Our findings show considerable spatial and temporal heterogeneity in the introduction and diffusion of the Alpha variant, both at the level of individual states and combined statistical areas, as it competes against the ancestral lineage. We discuss the key factors driving the time required for the Alpha variant to rise to dominance within a population, and quantify the impact that the emergence of the Alpha variant had on the effective reproduction number at the state level. Overall, we show that our multiscale modeling approach is able to capture the complexity and heterogeneity of the COVID-19 pandemic response in the US.

Abstract Exploring how the emergent functional connectivity (FC) relates to the underlying anatomy (structural connectivity, SC) is one of the major goals of modern neuroscience. At the macroscale level, no one-to-one correspondence between structural and functional links seems to exist. And we posit that to better understand their coupling, two key aspects should be considered: the directionality of the structural connectome and limitations in explaining networks functions through an undirected measure such as FC. Here, we employed an accurate directed SC of the mouse brain acquired through viral tracers and compared it with single-subject effective connectivity (EC) matrices derived from a dynamic causal model (DCM) applied to whole-brain resting-state fMRI data. We analyzed how SC deviates from EC and quantified their respective couplings by conditioning on the strongest SC links and EC links. We found that when conditioning on the strongest EC links, the obtained coupling follows the unimodal-transmodal functional hierarchy. Whereas the reverse is not true, as there are strong SC links within high-order cortical areas with no corresponding strong EC links. This mismatch is even more clear across networks; only within sensory motor networks did we observe connections that align in terms of both effective and structural strength.

Abstract Previous studies have adopted an edge-centric framework to study fine-scale network dynamics in human fMRI. To date, however, no studies have applied this framework to data collected from model organisms. Here, we analyze structural and functional imaging data from lightly anesthetized mice through an edge-centric lens. We find evidence of “bursty” dynamics and events - brief periods of high-amplitude network connectivity. Further, we show that on a per-frame basis events best explain static FC and can be divided into a series of hierarchically-related clusters. The co-fluctuation patterns associated with each cluster centroid link distinct anatomical areas and largely adhere to the boundaries of algorithmically detected functional brain systems. We then investigate the anatomical connectivity undergirding high-amplitude co-fluctuation patterns. We find that events induce modular bipartitions of the anatomical network of inter-areal axonal projections. Finally, we replicate these same findings in a human imaging dataset. In summary, this report recapitulates in a model organism many of the same phenomena observed in previously edge-centric analyses of human imaging data. However, unlike human subjects, the murine nervous system is amenable to invasive experimental perturbations. Thus, this study sets the stage for future investigation into the causal origins of fine-scale brain dynamics and high-amplitude co-fluctuations. Moreover, the cross-species consistency of the reported findings enhances the likelihood of future translation.

Abstract Most human activities require collaborations within and across formal or informal teams. Our understanding of how the collaborative efforts spent by teams relate to their performance is still a matter of debate. Teamwork results in a highly interconnected ecosystem of potentially overlapping components where tasks are performed in interaction with team members and across other teams. To tackle this problem, we propose a graph neural network model to predict a team’s performance while identifying the drivers determining such outcome. In particular, the model is based on three architectural channels: topological, centrality, and contextual, which capture different factors potentially shaping teams’ success. We endow the model with two attention mechanisms to boost model performance and allow interpretability. A first mechanism allows pinpointing key members inside the team. A second mechanism allows us to quantify the contributions of the three driver effects in determining the outcome performance. We test model performance on various domains, outperforming most classical and neural baselines. Moreover, we include synthetic datasets designed to validate how the model disentangles the intended properties on which our model vastly outperforms baselines.

Myeloproliferative neoplasms (MPNs) are subdivided into Philadelphia (Ph) chromosome-positive chronic myeloid leukemia (CML) and Ph-negative MPNs. BCR::ABL1 translocation is essential for the development and diagnosis of CML; on the other hand, the majority of Ph-negative MPNs are characterized by generally mutually exclusive mutations of Janus kinase 2 (JAK2), calreticulin (CALR), or thrombopoietin receptor/myeloproliferative leukemia (MPL). CALR mutations have been described essentially in JAK2 and MPL wild-type essential thrombocythemia and primary myelofibrosis. Rarely coexisting CALR and MPL mutations have been found in Ph-negative MPNs. BCR::ABL1 translocation and JAK2 mutations were initially considered mutually exclusive genomic events, but a discrete number of cases with the combination of these genetic alterations have been reported. The presence of BCR::ABL1 translocation with a coexisting CALR mutation is even more uncommon. Herein, starting from a routinely diagnosed case of CALR-mutated primary myelofibrosis subsequently acquiring BCR::ABL1 translocation, we performed a comprehensive review of the literature, discussing the clinicopathologic and molecular features, as well as the outcome and treatment of cases with BCR::ABL1 and CALR co-occurrence.

Pulmonary vasculitis identifies a heterogeneous group of diseases characterized by inflammation, damage and necrosis of the wall of pulmonary vessels. The most common approach to classify vasculitis is according to etiology, therefore dividing them into primary and secondary, with a further sub-classification of primary vasculitis based on the size of the affected vessels (large, medium, and small). Pulmonary involvement is frequently observed in patients with systemic vasculitis and radiological presentation is not pathognomonic, but may vary between diseases. The main findings using high-resolution computed tomography (HRCT) include small vessel wall thickening, nodular lesions, cavitary lesions, reticular opacities, ground-glass opacities (GGO), consolidations, interlobular septal thickening, tracheobronchial stenosis, and aneurysmal dilatation of pulmonary arteries, with or without pleural effusion. Radiological diagnosis alone is difficult since signs and symptoms of lung vessel involvement are often non-specific and might overlap with other conditions such as infections, connective tissue diseases and neoplasms. Therefore, the aim of this review is to describe the most common radiological features of lung involvement in pulmonary vasculitis so that, alongside detailed clinical history and laboratory tests, a prompt diagnosis can be performed.