The Brain-Gut Axis, an Important Player in Alzheimer and Parkinson Disease: A Narrative Review.

Neurodegenerative diseases, such as Alzheimer's disease (AD) and Parkinson's disease (PD), are severe age-related disorders with complex and multifactorial causes. Recent research suggests a critical link between neurodegeneration and the gut microbiome, via the gut-brain communication pathway. This review examines the role of trimethylamine N-oxide (TMAO), a gut microbiota-derived metabolite, in the development of AD and PD, and investigates its interaction with microRNAs (miRNAs) along this bidirectional pathway. TMAO, which is produced from dietary metabolites like choline and carnitine, has been linked to increased neuroinflammation, protein misfolding, and cognitive decline. In AD, elevated TMAO levels are associated with amyloid-beta and tau pathologies, blood-brain barrier disruption, and neuronal death. TMAO can cross the blood-brain barrier and promote the aggregation of amyloid and tau proteins. Similarly, TMAO affects alpha-synuclein conformation and aggregation, a hallmark of PD. TMAO also activates pro-inflammatory pathways such as NF-kB signaling, exacerbating neuroinflammation further. Moreover, TMAO modulates the expression of various miRNAs that are involved in neurodegenerative processes. Thus, the gut microbiome-miRNA-brain axis represents a newly discovered mechanistic link between gut dysbiosis and neurodegeneration. MiRNAs regulate the key pathways involved in neuroinflammation, oxidative stress, and neuronal death, contributing to disease progression. As a direct consequence, specific miRNA signatures may serve as potential biomarkers for the early detection and monitoring of AD and PD progression. This review aims to elucidate the complex interrelationships between the gut microbiota, trimethylamine-N-oxide (TMAO), microRNAs (miRNAs), and the central nervous system, and the implications of these connections in neurodegenerative diseases. In this context, an overview of the current neuroradiology techniques available for studying neuroinflammation and of the animal models used to investigate these intricate pathologies will also be provided. In summary, a bulk of evidence supports the concept that modulating the gut-brain communication pathway through dietary changes, the manipulation of the microbiome, and/or miRNA-based therapies may offer novel approaches for implementing the treatment of debilitating neurological disorders.

Long-access heroin self-administration induces region specific reduction of grey matter volume and microglia reactivity in the rat.

In opioid use disorder (OUD) patients, a decrease in brain grey matter volume (GMV) has been reported. It is unclear whether this is the consequence of prolonged exposure to opioids or is a predisposing causal factor in OUD development. To investigate this, we conducted a structural MRI longitudinal study in NIH Heterogeneous Stock rats exposed to heroin self-administration and age-matched naïve controls housed in the same controlled environment. Structural MRI scans were acquired before (MRI1) and after (MRI2) a prolonged period of long access heroin self-administration resulting in escalation of drug intake. Heroin intake resulted in reduced GMV in various cortical and sub-cortical brain regions. In drug-naïve controls no difference was found between MRI1 and MRI2. Notably, the degree of GMV reduction in the medial prefrontal cortex (mPFC) and the insula positively correlated with the amount of heroin consumed and the escalation of heroin use. In a preliminary gene expression analysis, we identified a number of transcripts linked to immune response and neuroinflammation. This prompted us to hypothesize a link between changes in microglia homeostasis and loss of GMV. For this reason, we analyzed the number and morphology of microglial cells in the mPFC and insula. The number of neurons and their morphology was also evaluated. The primary motor cortex, where no GMV change was observed, was used as negative control. We found no differences in the number of neurons and microglia cells following heroin. However, in the same regions where reduced GMV was detected, we observed a shift towards a rounder shape and size reduction in microglia, suggestive of their homeostatic change towards a reactive state. Altogether these findings suggest that escalation of heroin intake correlates with loss of GMV in specific brain regions and that this phenomenon is linked to changes in microglial morphology.

Long-access heroin self-administration induces region specific reduction of grey matter volume and microglia reactivity in the rat.

In opioid use disorder (OUD) patients, a decrease in brain grey matter volume (GMV) has been reported. It is unclear whether this is the consequence of prolonged exposure to opioids or is a predisposing causal factor in OUD development. To investigate this, we conducted a structural MRI longitudinal study in NIH Heterogeneous Stock rats exposed to heroin self-administration and age-matched naïve controls housed in the same controlled environment. Structural MRI scans were acquired before (MRI 1 ) and after (MRI 2 ) a prolonged period of long access heroin self-administration resulting in escalation of drug intake. Heroin intake resulted in reduced GMV in various cortical and sub-cortical brain regions. In drug-naïve controls no difference was found between MRI 1 and MRI 2 . Notably, the degree of GMV reduction in the medial prefrontal cortex (mPFC) and the insula positively correlated with the amount of heroin consumed and the escalation of heroin use. In a preliminary gene expression analysis, we identified a number of transcripts linked to immune response and neuroinflammation. This prompted us to hypothesize a link between changes in microglia homeostasis and loss of GMV. For this reason, we analyzed the number and morphology of microglial cells in the mPFC and insula. The number of neurons and their morphology was also evaluated. The primary motor cortex, where no GMV change was observed, was used as negative control. We found no differences in the number of neurons and microglia cells following heroin. However, in the same regions where reduced GMV was detected, we observed a shift towards a rounder shape and size reduction in microglia, suggestive of their homeostatic change towards a reactive state. Altogether these findings suggest that escalation of heroin intake correlates with loss of GMV in specific brain regions and that this phenomenon is linked to changes in microglial morphology.

Manganese-enhanced magnetic resonance imaging reveals light-induced brain asymmetry in embryo.

The idea that sensory stimulation to the embryo (in utero or in ovo) may be crucial for brain development is widespread. Unfortunately, up to now evidence was only indirect because mapping of embryonic brain activity in vivo is challenging. Here, we applied for the first time manganese enhanced magnetic resonance imaging (MEMRI), a functional imaging method, to the eggs of domestic chicks. We revealed light-induced brain asymmetry by comparing embryonic brain activity in vivo of eggs that were stimulated by light or maintained in the darkness. Our protocol paves the way to investigation of the effects of a variety of sensory stimulations on brain activity in embryo.

Advances in Stabilization and Enrichment of Shallow Nitrogen-Vacancy Centers in Diamond for Biosensing and Spin-Polarization Transfer.

Negatively charged nitrogen-vacancy (NV-) centers in diamond have unique magneto-optical properties, such as high fluorescence, single-photon generation, millisecond-long coherence times, and the ability to initialize and read the spin state using purely optical means. This makes NV- centers a powerful sensing tool for a range of applications, including magnetometry, electrometry, and thermometry. Biocompatible NV-rich nanodiamonds find application in cellular microscopy, nanoscopy, and in vivo imaging. NV- centers can also detect electron spins, paramagnetic agents, and nuclear spins. Techniques have been developed to hyperpolarize 14N, 15N, and 13C nuclear spins, which could open up new perspectives in NMR and MRI. However, defects on the diamond surface, such as hydrogen, vacancies, and trapping states, can reduce the stability of NV- in favor of the neutral form (NV0), which lacks the same properties. Laser irradiation can also lead to charge-state switching and a reduction in the number of NV- centers. Efforts have been made to improve stability through diamond substrate doping, proper annealing and surface termination, laser irradiation, and electric or electrochemical tuning of the surface potential. This article discusses advances in the stabilization and enrichment of shallow NV- ensembles, describing strategies for improving the quality of diamond devices for sensing and spin-polarization transfer applications. Selected applications in the field of biosensing are discussed in more depth.

Amplifying the Effects of Contrast Agents on Magnetic Resonance Images Using a Deep Learning Method Trained on Synthetic Data.

OBJECTIVES: Artificial intelligence (AI) methods can be applied to enhance contrast in diagnostic images beyond that attainable with the standard doses of contrast agents (CAs) normally used in the clinic, thus potentially increasing diagnostic power and sensitivity. Deep learning-based AI relies on training data sets, which should be sufficiently large and diverse to effectively adjust network parameters, avoid biases, and enable generalization of the outcome. However, large sets of diagnostic images acquired at doses of CA outside the standard-of-care are not commonly available. Here, we propose a method to generate synthetic data sets to train an "AI agent" designed to amplify the effects of CAs in magnetic resonance (MR) images. The method was fine-tuned and validated in a preclinical study in a murine model of brain glioma, and extended to a large, retrospective clinical human data set. MATERIALS AND METHODS: A physical model was applied to simulate different levels of MR contrast from a gadolinium-based CA. The simulated data were used to train a neural network that predicts image contrast at higher doses. A preclinical MR study at multiple CA doses in a rat model of glioma was performed to tune model parameters and to assess fidelity of the virtual contrast images against ground-truth MR and histological data. Two different scanners (3 T and 7 T, respectively) were used to assess the effects of field strength. The approach was then applied to a retrospective clinical study comprising 1990 examinations in patients affected by a variety of brain diseases, including glioma, multiple sclerosis, and metastatic cancer. Images were evaluated in terms of contrast-to-noise ratio and lesion-to-brain ratio, and qualitative scores. RESULTS: In the preclinical study, virtual double-dose images showed high degrees of similarity to experimental double-dose images for both peak signal-to-noise ratio and structural similarity index (29.49 dB and 0.914 dB at 7 T, respectively, and 31.32 dB and 0.942 dB at 3 T) and significant improvement over standard contrast dose (ie, 0.1 mmol Gd/kg) images at both field strengths. In the clinical study, contrast-to-noise ratio and lesion-to-brain ratio increased by an average 155% and 34% in virtual contrast images compared with standard-dose images. Blind scoring of AI-enhanced images by 2 neuroradiologists showed significantly better sensitivity to small brain lesions compared with standard-dose images (4.46/5 vs 3.51/5). CONCLUSIONS: Synthetic data generated by a physical model of contrast enhancement provided effective training for a deep learning model for contrast amplification. Contrast above that attainable at standard doses of gadolinium-based CA can be generated through this approach, with significant advantages in the detection of small low-enhancing brain lesions.

Divergent Effects of Laser Irradiation on Ensembles of Nitrogen-Vacancy Centers in Bulk and Nanodiamonds: Implications for Biosensing.

Ensembles of negatively charged nitrogen-vacancy centers (NV-) in diamond have been proposed for sensing of magnetic fields and paramagnetic agents, and as a source of spin-order for the hyperpolarization of nuclei in magnetic resonance applications. To this end, strongly fluorescent nanodiamonds (NDs) represent promising materials, with large surface areas and dense ensembles of NV-. However, surface effects tend to favor the less useful neutral form, the NV0 centers, and strategies to increase the density of shallow NV- centers have been proposed, including irradiation with strong laser power (Gorrini in ACS Appl Mater Interfaces. 13:43221-43232, 2021). Here, we study the fluorescence properties and optically detected magnetic resonance (ODMR) of NV- centers as a function of laser power in strongly fluorescent bulk diamond and in nanodiamonds obtained by nanomilling of the native material. In bulk diamond, we find that increasing laser power increases ODMR contrast, consistent with a power-dependent increase in spin-polarization. Conversely, in nanodiamonds we observe a non-monotonic behavior, with a decrease in ODMR contrast at higher laser power. We hypothesize that this phenomenon may be ascribed to more efficient NV-→NV0 photoconversion in nanodiamonds compared to bulk diamond, resulting in depletion of the NV- pool. A similar behavior is shown for NDs internalized in macrophage cells under the typical experimental conditions of imaging bioassays. Our results suggest strong laser irradiation is not an effective strategy in NDs, where the interplay between surface effects and local microenvironment determine the optimal experimental conditions.

From a systems view to spotting a hidden island: A narrative review implicating insula function in alcoholism.

Excessive use of alcohol promotes the development of alcohol addiction, but the understanding of how alcohol-induced brain alterations lead to addiction remains limited. To further this understanding, we adopted an unbiased discovery strategy based on the principles of systems medicine. We used functional magnetic resonance imaging data from patients and animal models of alcohol addiction-like behaviors, and developed mathematical models of the 'relapse-prone' network states to identify brain sites and functional networks that can be selectively targeted by therapeutic interventions. Our systems level, non-local, and largely unbiased analyses converged on a few well-defined brain regions, with the insula emerging as one of the most consistent findings across studies. In proof-of-concept experiments we were able to demonstrate that it is possible to guide network dynamics towards increased resilience in animals but an initial translation into a clinical trial targeting the insula failed. Here, in a narrative review, we summarize the key experiments, methodological developments and knowledge gained from this complete round of a discovery cycle moving from identification of 'relapse-prone' network states in humans and animals to target validation and intervention trial. Future concerted efforts are necessary to gain a deeper understanding of insula function a in a state-dependent, circuit-specific and cell population perspective, and to develop the means for insula-directed interventions, before therapeutic targeting of this structure may become possible.

Increased network centrality of the anterior insula in early abstinence from alcohol.

Abnormal resting-state functional connectivity, as measured by functional magnetic resonance imaging (MRI), has been reported in alcohol use disorders (AUD), but findings are so far inconsistent. Here, we exploited recent developments in graph-theoretical analyses, enabling improved resolution and fine-grained representation of brain networks, to investigate functional connectivity in 35 recently detoxified alcohol dependent patients versus 34 healthy controls. Specifically, we focused on the modular organization, that is, the presence of tightly connected substructures within a network, and on the identification of brain regions responsible for network integration using an unbiased approach based on a large-scale network composed of more than 600 a priori defined nodes. We found significant reductions in global connectivity and region-specific disruption in the network topology in patients compared with controls. Specifically, the basal brain and the insular-supramarginal cortices, which form tightly coupled modules in healthy subjects, were fragmented in patients. Further, patients showed a strong increase in the centrality of the anterior insula, which exhibited stronger connectivity to distal cortical regions and weaker connectivity to the posterior insula. Anterior insula centrality, a measure of the integrative role of a region, was significantly associated with increased risk of relapse. Exploratory analysis suggests partial recovery of modular structure and insular connectivity in patients after 2 weeks. These findings support the hypothesis that, at least during the early stages of abstinence, the anterior insula may drive exaggerated integration of interoceptive states in AUD patients with possible consequences for decision making and emotional states and that functional connectivity is dynamically changing during treatment.

Long-Lived Ensembles of Shallow NV- Centers in Flat and Nanostructured Diamonds by Photoconversion.

Shallow, negatively charged nitrogen-vacancy centers (NV-) in diamond have been proposed for high-sensitivity magnetometry and spin-polarization transfer applications. However, surface effects tend to favor and stabilize the less useful neutral form, the NV0 centers. Here, we report the effects of green laser irradiation on ensembles of nanometer-shallow NV centers in flat and nanostructured diamond surfaces as a function of laser power in a range not previously explored (up to 150 mW/µm2). Fluorescence spectroscopy, optically detected magnetic resonance (ODMR), and charge-photoconversion detection are applied to characterize the properties and dynamics of NV- and NV0 centers. We demonstrate that high laser power strongly promotes photoconversion of NV0 to NV- centers. Surprisingly, the excess NV- population is stable over a timescale of 100 ms after switching off the laser, resulting in long-lived enrichment of shallow NV-. The beneficial effect of photoconversion is less marked in nanostructured samples. Our results are important to inform the design of samples and experimental procedures for applications relying on ensembles of shallow NV- centers in diamond.

Neurochemical underpinning of hemodynamic response to neuropsychiatric drugs: A meta- and cluster analysis of preclinical studies.

Functional magnetic resonance imaging (fMRI) is an extensively used method for the investigation of normal and pathological brain function. In particular, fMRI has been used to characterize spatiotemporal hemodynamic response to pharmacological challenges as a non-invasive readout of neuronal activity. However, the mechanisms underlying regional signal changes are yet unclear. In this study, we use a meta-analytic approach to converge data from microdialysis experiments with relative cerebral blood volume (rCBV) changes following acute administration of neuropsychiatric drugs in adult male rats. At whole-brain level, the functional response patterns show very weak correlation with neurochemical alterations, while for numerous brain areas a strong positive correlation with noradrenaline release exists. At a local scale of individual brain regions, the rCBV response to neurotransmitters is anatomically heterogeneous and, importantly, based on a complex interplay of different neurotransmitters that often exert opposing effects, thus providing a mechanism for regulating and fine tuning hemodynamic responses in specific regions.

Laser-Synthesis of NV-Centers-Enriched Nanodiamonds: Effect of Different Nitrogen Sources.

Due to the large number of possible applications in quantum technology fields-especially regarding quantum sensing-of nitrogen-vacancy (NV) centers in nanodiamonds (NDs), research on a cheap, scalable and effective NDs synthesis technique has acquired an increasing interest. Standard production methods, such as detonation and grinding, require multistep post-synthesis processes and do not allow precise control in the size and fluorescence intensity of NDs. For this reason, a different approach consisting of pulsed laser ablation of carbon precursors has recently been proposed. In this work, we demonstrate the synthesis of NV-fluorescent NDs through pulsed laser ablation of an N-doped graphite target. The obtained NDs are fully characterized in the morphological and optical properties, in particular with optically detected magnetic resonance spectroscopy to unequivocally prove the NV origin of the NDs photoluminescence. Moreover, to compare the different fluorescent NDs laser-ablation-based synthesis techniques recently developed, we report an analysis of the effect of the medium in which laser ablation of graphite is performed. Along with it, thermodynamic aspects of the physical processes occurring during laser irradiation are analyzed. Finally, we show that the use of properly N-doped graphite as a target for laser ablation can lead to precise control in the number of NV centers in the produced NDs.

Anterior insula stimulation suppresses appetitive behavior while inducing forebrain activation in alcohol-preferring rats.

The anterior insular cortex plays a key role in the representation of interoceptive effects of drug and natural rewards and their integration with attention, executive function, and emotions, making it a potential target region for intervention to control appetitive behaviors. Here, we investigated the effects of chemogenetic stimulation or inhibition of the anterior insula on alcohol and sucrose consumption. Excitatory or inhibitory designer receptors (DREADDs) were expressed in the anterior insula of alcohol-preferring rats by means of adenovirus-mediated gene transfer. Rats had access to either alcohol or sucrose solution during intermittent sessions. To characterize the brain network recruited by chemogenetic insula stimulation we measured brain-wide activation patterns using pharmacological magnetic resonance imaging (phMRI) and c-Fos immunohistochemistry. Anterior insula stimulation by the excitatory Gq-DREADDs significantly attenuated both alcohol and sucrose consumption, whereas the inhibitory Gi-DREADDs had no effects. In contrast, anterior insula stimulation failed to alter locomotor activity or deprivation-induced water drinking. phMRI and c-Fos immunohistochemistry revealed downstream activation of the posterior insula and medial prefrontal cortex, as well as of the mediodorsal thalamus and amygdala. Our results show the critical role of the anterior insula in regulating reward-directed behavior and delineate an insula-centered functional network associated with the effects of insula stimulation. From a translational perspective, our data demonstrate the therapeutic potential of circuit-based interventions and suggest that potentiation of insula excitability with neuromodulatory methods, such as repetitive transcranial magnetic stimulation (rTMS), could be useful in the treatment of alcohol use disorders.

Scale-resolved analysis of brain functional connectivity networks with spectral entropy.

Functional connectivity is derived from inter-regional correlations in spontaneous fluctuations of brain activity, and can be represented in terms of complete graphs with continuous (real-valued) edges. The structure of functional connectivity networks is strongly affected by signal processing procedures to remove the effects of motion, physiological noise and other sources of experimental error. However, in the absence of an established ground truth, it is difficult to determine the optimal procedure, and no consensus has been reached on the most effective approach to remove nuisance signals without unduly affecting the network intrinsic structural features. Here, we use a novel information-theoretic approach, based on von Neumann entropy, which provides a measure of information encoded in the networks at different scales. We also define a measure of distance between networks, based on information divergence, and optimal null models appropriate for the description of functional connectivity networks, to test for the presence of nontrivial structural patterns that are not the result of simple local constraints. This formalism enables a scale-resolved analysis of the distance between a functional connectivity network and its maximally random counterpart, thus providing a means to assess the effects of noise and image processing on network structure. We apply this novel approach to address a few open questions in the analysis of brain functional connectivity networks. Specifically, we demonstrate a strongly beneficial effect of network sparsification by removal of the weakest links, and the existence of an optimal threshold that maximizes the ability to extract information on large-scale network structures. Additionally, we investigate the effects of different degrees of motion at different scales, and compare the most popular processing pipelines designed to mitigate its deleterious effect on functional connectivity networks. We show that network sparsification, in combination with motion correction algorithms, dramatically improves detection of large scale network structure.

Aberrant insular cortex connectivity in abstinent alcohol-dependent rats is reversed by dopamine D3 receptor blockade.

A few studies have reported aberrant functional connectivity in alcoholic patients, but the specific neural circuits involved remain unknown. Moreover, it is unclear whether these alterations can be reversed upon treatment. Here, we used functional MRI to study resting state connectivity in rats following chronic intermittent exposure to ethanol. Further, we evaluated the effects of SB-277011-a, a selective dopamine D3 receptor antagonist, known to decrease ethanol consumption. Alcohol-dependent and control rats (N = 13/14 per group), 3 weeks into abstinence, were administered SB-277011-a or vehicle before fMRI sessions. Resting state connectivity networks were extracted by independent component analysis. A dual-regression analysis was performed using independent component maps as spatial regressors, and the effects of alcohol history and treatment on connectivity were assessed. A history of alcohol dependence caused widespread reduction of the internal coherence of components. Weaker correlation was also found between the insula cortex (IC) and cingulate cortices, key constituents of the salience network. Similarly, reduced connectivity was observed between a component comprising the anterior insular cortex, together with the caudate putamen (CPu-AntIns), and the posterior part of the IC. On the other hand, postdependent rats showed strengthened connectivity between salience and reward networks. In particular, higher connectivity was observed between insula and nucleus accumbens, between the ventral tegmental area and the cingulate cortex and between the VTA and CPu-AntIns. Interestingly, aberrant connectivity in postdependent rats was partially restored by acute administration of SB-277011-a, which, conversely, had no significant effects in naïve rats.

Apomorphine-induced reorganization of striato-frontal connectivity in patients with tremor-dominant Parkinson's disease.

INTRODUCTION: Apomorphine is a dopamine agonist used in Parkinson's disease (PD), which matches levodopa in terms of the magnitude of effect on the cardinal motor features, such as tremor and bradykinesia. The beneficial effect of this treatment on PD patients with tremor-dominant has widely been demonstrated, although the underlying neural correlates are unknown. We sought to examine the effects of apomorphine on topological characteristics of resting-state functional connectivity networks in tremor-dominant PD (tdPD) patients. METHODS: Sixteen tdPD patients were examined using a combined electromyography-functional magnetic resonance imaging approach. Patients were scanned twice following either placebo (subcutaneous injection of 1 mL saline solution) or 1 mg of apomorphine injection. Graph analysis methods were employed to investigate the modular organization of functional connectivity networks before and after drug treatment. RESULTS: After injection of apomorphine, evident reduction of tremor symptoms was mirrored by a significant increase in overall connectivity strength and reorganization of the modular structure of the basal ganglia and of the fronto-striatal module. Moreover, we found an increase in the centrality of motor and premotor regions. No differences were found between pre- and post-placebo sessions. CONCLUSION: These results provide new evidence about the effects of apomorphine at a large-scale neural network level showing that drug treatment modifies the brain functional organization of tdPD, increasing the overall resting-state functional connectivity strength, the segregation of striato-frontal regions and the integrative role of motor areas.

Building better strategies to develop new medications in Alcohol Use Disorder: Learning from past success and failure to shape a brighter future.

Alcohol Use Disorder (AUD) is a chronic disease that develops over the years. The complexity of the neurobiological processes contributing to the emergence of AUD and the neuroadaptive changes occurring during disease progression make it difficult to improve treatments. On the other hand, this complexity offers researchers the possibility to explore new targets. Over years of intense research several molecules were tested in AUD; in most cases, despite promising preclinical data, the clinical efficacy appeared insufficient to justify futher development. A prototypical example is that of corticotropin releasing factor type 1 receptor (CRF1R) antagonists that showed significant effectiveness in animal models of AUD but were largely ineffective in humans. The present article attempts to analyze the most recent venues in the development of new medications in AUD with a focus on the most promising drug targets under current exploration. Moreover, we delineate the importance of using a more integrated translational framework approach to correlate preclinical findings and early clinical data to enhance the probability to validate biological targets of interest.

Segmented Echo Planar Imaging Improves Detection of Subcortical Functional Connectivity Networks in the Rat Brain.

Susceptibility artifacts in the vicinity of aural and nasal cavities result in significant signal drop-out and image distortion in echo planar imaging of the rat brain. These effects may limit the study of resting state functional connectivity in deep brain regions. Here, we explore the use of segmented EPI for resting state fMRI studies in the rat, and assess the relative merits of this method compared to single shot EPI. Sequences were evaluated in terms of signal-to-noise ratio, geometric distortions, data driven detection of resting state networks and group level correlations of time series. Multishot imaging provided improved SNR, temporal SNR and reduced geometric distortion in deep areas, while maintaining acceptable overall image quality in cortical regions. Resting state networks identified by independent component analysis were consistent across methods, but multishot EPI provided a more robust and accurate delineation of connectivity patterns involving deep regions typically affected by susceptibility artifacts. Importantly, segmented EPI showed reduced between-subject variability and stronger statistical significance of pairwise correlations at group level over the whole brain and in particular in subcortical regions. Multishot EPI may represent a valid alternative to snapshot methods in functional connectivity studies, particularly for the investigation of subcortical regions and deep gray matter nuclei.

Thermodynamics of network model fitting with spectral entropies.

An information-theoretic approach inspired by quantum statistical mechanics was recently proposed as a means to optimize network models and to assess their likelihood against synthetic and real-world networks. Importantly, this method does not rely on specific topological features or network descriptors but leverages entropy-based measures of network distance. Entertaining the analogy with thermodynamics, we provide a physical interpretation of model hyperparameters and propose analytical procedures for their estimate. These results enable the practical application of this novel and powerful framework to network model inference. We demonstrate this method in synthetic networks endowed with a modular structure and in real-world brain connectivity networks.

Ring-opening copolymerization thermodynamics and kinetics of γ-valerolactone/ϵ-caprolactone.

The general misconception that γ-lactones are not thermodynamically polymerizable has limited the development of all γ-lactone-based copolymers. A few studies have reported copolymerization of these five-membered cyclic esters with more reactive monomers, yet a systematic investigation of kinetics and thermodynamics is still lacking. To explore the feasibility of the reaction, we combined equilibrium and non-isothermal syntheses for the copolymerization of γ-valerolactone with ϵ-caprolactone, initiated with methoxy polyethyleneglycol and catalyzed by Tin(II) 2-ethylhexanoate. Here, we present the polymerization kinetic and thermodynamic parameters for different monomer ratios in the reaction feed. We observed the dependency of enthalpy and entropy of polymerization upon monomer ratio changes, and estimated a linear increase in the activation energy by increasing the γ-valerolactone fraction in the starting monomer mixture. Our data demonstrate that γ-valerolactone can copolymerize with ϵ-caprolactone, but only under specific conditions. The reaction parameters determined in this study will enable preparation of additional γ-valerolactone-based copolymers and development of a family of degradable materials with improved properties in respect to commonly used polyesters.