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Decades of neuroimaging studies have shown modest differences in brain structure and connectivity in depression, hindering mechanistic insights or the identification of risk factors for disease onset 1 . Furthermore, whereas depression is episodic, few longitudinal neuroimaging studies exist, limiting understanding of mechanisms that drive mood-state transitions. The emerging field of precision functional mapping has used densely sampled longitudinal neuroimaging data to show behaviourally meaningful differences in brain network topography and connectivity between and in healthy individuals 2-4 , but this approach has not been applied in depression. Here, using precision functional mapping and several samples of deeply sampled individuals, we found that the frontostriatal salience network is expanded nearly twofold in the cortex of most individuals with depression. This effect was replicable in several samples and caused primarily by network border shifts, with three distinct modes of encroachment occurring in different individuals. Salience network expansion was stable over time, unaffected by mood state and detectable in children before the onset of depression later in adolescence. Longitudinal analyses of individuals scanned up to 62 times over 1.5 years identified connectivity changes in frontostriatal circuits that tracked fluctuations in specific symptoms and predicted future anhedonia symptoms. Together, these findings identify a trait-like brain network topology that may confer risk for depression and mood-state-dependent connectivity changes in frontostriatal circuits that predict the emergence and remission of depressive symptoms over time., (© 2024. The Author(s).)

Motor-task functional magnetic resonance imaging (fMRI) is crucial in the study of several clinical conditions, including stroke and Parkinson's disease. However, motor-task fMRI is complicated by task-correlated head motion, which can be magnified in clinical populations and confounds motor activation results. One method that may mitigate this issue is multi-echo independent component analysis (ME-ICA), which has been shown to separate the effects of head motion from the desired blood oxygenation level dependent (BOLD) signal but has not been tested in motor-task datasets with high amounts of motion. In this study, we collected an fMRI dataset from a healthy population who performed a hand grasp task with and without task-correlated amplified head motion to simulate a motor-impaired population. We analyzed these data using three models: single-echo (SE), multi-echo optimally combined (ME-OC), and ME-ICA. We compared the models' performance in mitigating the effects of head motion on the subject level and group level. On the subject level, ME-ICA better dissociated the effects of head motion from the BOLD signal and reduced noise. Both ME models led to increased t-statistics in brain motor regions. In scans with high levels of motion, ME-ICA additionally mitigated artifacts and increased stability of beta coefficient estimates, compared to SE. On the group level, all three models produced activation clusters in expected motor areas in scans with both low and high motion, indicating that group-level averaging may also sufficiently resolve motion artifacts that vary by subject. These findings demonstrate that ME-ICA is a useful tool for subject-level analysis of motor-task data with high levels of task-correlated head motion. The improvements afforded by ME-ICA are critical to improve reliability of subject-level activation maps for clinical populations in which group-level analysis may not be feasible or appropriate, for example, in a chronic stroke cohort with varying stroke location and degree of tissue damage., Competing Interests: DECLARATION OF COMPETING INTEREST The authors declare no competing financial interests.

Cerebrovascular reactivity (CVR), defined as the cerebral blood flow response to a vasoactive stimulus, is an imaging biomarker with demonstrated utility in a range of diseases and in typical development and aging processes. A robust and widely implemented method to map CVR involves using a breath-hold task during a BOLD fMRI scan. Recording end-tidal CO 2 (P ET CO 2 ) changes during the breath-hold task is recommended to be used as a reference signal for modeling CVR amplitude in standard units (%BOLD/mmHg) and CVR delay in seconds. However, obtaining reliable P ET CO 2 recordings requires equipment and task compliance that may not be achievable in all settings. To address this challenge, we investigated two alternative reference signals to map CVR amplitude and delay in a lagged general linear model (lagged-GLM) framework: respiration volume per time (RVT) and average gray matter BOLD response (GM-BOLD). In 8 healthy adults with multiple scan sessions, we compare spatial agreement of CVR maps from RVT and GM-BOLD to those generated with P ET CO 2 . We define a threshold to determine whether a P ET CO 2 recording has "sufficient" quality for CVR mapping and perform these comparisons in 16 datasets with sufficient P ET CO 2 and 6 datasets with insufficient P ET CO 2 . When P ET CO 2 quality is sufficient, both RVT and GM-BOLD produce CVR amplitude maps that are nearly identical to those from P ET CO 2 (after accounting for differences in scale), with the caveat they are not in standard units to facilitate between-group comparisons. CVR delays are comparable to P ET CO 2 with an RVT regressor but may be underestimated with the average GM-BOLD regressor. Importantly, when P ET CO 2 quality is insufficient, RVT and GM-BOLD CVR recover reasonable CVR amplitude and delay maps, provided the participant attempted the breath-hold task. Therefore, our framework offers a solution for achieving high quality CVR maps in both retrospective and prospective studies where sufficient P ET CO 2 recordings are not available and especially in populations where obtaining reliable measurements is a known challenge (e.g., children). Our results have the potential to improve the accessibility of CVR mapping and to increase the prevalence of this promising metric of vascular health., Competing Interests: Declaration of Competing Interest The authors declare no competing financial interests., (Copyright © 2023. Published by Elsevier Inc.)

Cerebrovascular reactivity (CVR), an important indicator of cerebrovascular health, is commonly studied with the Blood Oxygenation Level Dependent functional MRI (BOLD-fMRI) response to a vasoactive stimulus. Theoretical and empirical evidence suggests that baseline cerebral blood flow (CBF) modulates BOLD signal amplitude and may influence BOLD-CVR estimates. We address how acquisition and modeling choices affect the relationship between baseline cerebral blood flow (bCBF) and BOLD-CVR: whether BOLD-CVR is modeled with the inclusion of a breathing task, and whether BOLD-CVR amplitudes are optimized for hemodynamic lag effects. We assessed between-subject correlations of average GM values and within-subject spatial correlations across cortical regions. Our results suggest that a breathing task addition to a resting-state acquisition, alongside lag-optimization within BOLD-CVR modeling, can improve BOLD-CVR correlations with bCBF, both between- and within-subjects, likely because these CVR estimates are more physiologically accurate. We report positive correlations between bCBF and BOLD-CVR, both between- and within-subjects. The physiological explanation of this positive correlation is unclear; research with larger samples and tightly controlled vasoactive stimuli is needed. Insights into what drives variability in BOLD-CVR measurements and related measurements of cerebrovascular function are particularly relevant when interpreting results in populations with altered vascular and/or metabolic baselines or impaired cerebrovascular reserve., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Stickland, Zvolanek, Moia, Caballero-Gaudes and Bright.)

Analyses of brain function and anatomy using shared neuroimaging data is an important development, and have acquired the potential to be scaled up with the specification of a new Brain Imaging Data Structure (BIDS) standard. To date, a variety of software tools help researchers in converting their source data to BIDS but often require programming skills or are tailored to specific institutes, data sets, or data formats. In this paper, we introduce BIDScoin, a cross-platform, flexible, and user-friendly converter that provides a graphical user interface (GUI) to help users finding their way in BIDS standard. BIDScoin does not require programming skills to be set up and used and supports plugins to extend their functionality. In this paper, we show its design and demonstrate how it can be applied to a downloadable tutorial data set. BIDScoin is distributed as free and open-source software to foster the community-driven effort to promote and facilitate the use of BIDS standard., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zwiers, Moia and Oostenveld.)

Cerebrovascular reactivity (CVR), defined here as the Blood Oxygenation Level Dependent (BOLD) response to a CO 2 pressure change, is a useful metric of cerebrovascular function. Both the amplitude and the timing (hemodynamic lag) of the CVR response can bring insight into the nature of a cerebrovascular pathology and aid in understanding noise confounds when using functional Magnetic Resonance Imaging (fMRI) to study neural activity. This research assessed a practical modification to a typical resting-state fMRI protocol, to improve the characterization of cerebrovascular function. In 9 healthy subjects, we modelled CVR and lag in three resting-state data segments, and in data segments which added a 2-3 minute breathing task to the start of a resting-state segment. Two different breathing tasks were used to induce fluctuations in arterial CO 2 pressure: a breath-hold task to induce hypercapnia (CO 2 increase) and a cued deep breathing task to induce hypocapnia (CO 2 decrease). Our analysis produced voxel-wise estimates of the amplitude (CVR) and timing (lag) of the BOLD-fMRI response to CO 2 by systematically shifting the CO 2 regressor in time to optimize the model fit. This optimization inherently increases gray matter CVR values and fit statistics. The inclusion of a simple breathing task, compared to a resting-state scan only, increases the number of voxels in the brain that have a significant relationship between CO 2 and BOLD-fMRI signals, and improves our confidence in the plausibility of voxel-wise CVR and hemodynamic lag estimates. We demonstrate the clinical utility and feasibility of this protocol in an incidental finding of Moyamoya disease, and explore the possibilities and challenges of using this protocol in younger populations. This hybrid protocol has direct applications for CVR mapping in both research and clinical settings and wider applications for fMRI denoising and interpretation., Competing Interests: Declaration of Competing Interest The authors declare no competing financial interests., (Copyright © 2021. Published by Elsevier Inc.)

Neuroscience studies entail the generation of massive collections of heterogeneous data (e.g. demographics, clinical records, medical images). Integration and analysis of such data in research centers is pivotal for elucidating disease mechanisms and improving clinical outcomes. However, data collection in clinics often relies on non-standardized methods, such as paper-based documentation. Moreover, diverse data types are collected in different departments hindering efficient data organization, secure sharing and compliance to the FAIR (Findable, Accessible, Interoperable, Reusable) principles. Henceforth, in this manuscript we present a specialized data management system designed to enhance research workflows in Deep Brain Stimulation (DBS), a state-of-the-art neurosurgical procedure employed to treat symptoms of movement and psychiatric disorders. The system leverages REDCap to promote accurate data capture in hospital settings and secure sharing with research institutes, Brain Imaging Data Structure (BIDS) as image storing standard and a DBS-specific SQLite database as comprehensive data store and unified interface to all data types. A self-developed Python tool automates the data flow between these three components, ensuring their full interoperability. The proposed framework has already been successfully employed for capturing and analyzing data of 107 patients from 2 medical institutions. It effectively addresses the challenges of managing, sharing and retrieving diverse data types, fostering advancements in data quality, organization, analysis, and collaboration among medical and research institutions. [ABSTRACT FROM AUTHOR]

Halide perovskites are a class of materials of consolidated optoelectronic and electrochemical applications, reaching efficiencies compared to established materials in respective fields. In this scenario, the design and understanding of composition–structure–property relations is imperative. In solid solutions containing mixed cations, some direct relations between the sizes of the substituents and the properties of perovskites are generally observed. However, in several cases, these relations are not observed, implying that other characteristics of these cations play a major role. Despite its importance, this understanding has not been comprehensively deepened. To address this issue, we synthesized and characterized the structure, electrical behavior, and stability of methylammonium lead iodide-based perovskites with equal amounts of the substituents guanidinium, ethylammonium, and acetamidinium. These three large organic cations have essentially equal sizes but other remarkably different characteristics, such as the number of N–H bonds, intrinsic dipole moment, and order of C–N bonds. Herein, we show that these cations have dramatically different effects over important fundamental and applied properties of resulting perovskites, including the orthorhombic-to-tetragonal and tetragonal-to-cubic phase transitions, microstructural development, ionic conductivity, I–V hysteresis, electronic carrier mobility, and stability against light-induced degradation. These effects are correlated with the characteristics of the large substituent cations and help pave the way for a better rational chemical design of halide perovskites. [ABSTRACT FROM AUTHOR]

Background: This study aimed to explore the characteristics of abnormal regional resting-state functional magnetic resonance imaging (rs-fMRI) activity in comatose patients in the early period after cardiac arrest (CA), and to investigate their relationships with neurological outcomes. We also explored the correlations between jugular venous oxygen saturation (SjvO2) and rs-fMRI activity in resuscitated comatose patients. We also examined the relationship between the amplitude of the N20-baseline and the rs-fMRI activity within the intracranial conduction pathway of somatosensory evoked potentials (SSEPs). Methods: Between January 2021 and January 2024, eligible post-resuscitated patients were screened to undergo fMRI examination. The amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) of rs-fMRI blood oxygenation level-dependent (BOLD) signals were used to characterize regional neural activity. Neurological outcomes were evaluated using the Glasgow–Pittsburgh cerebral performance category (CPC) scale at 3 months after CA. Results: In total, 20 healthy controls and 31 post-resuscitated patients were enrolled in this study. The rs-fMRI activity of resuscitated patients revealed complex changes, characterized by increased activity in some local brain regions and reduced activity in others compared to healthy controls (P < 0.05). However, the mean ALFF values of the whole brain were significantly greater in CA patients (P = 0.011). Among the clusters of abnormal rs-fMRI activity, the cluster values of ALFF in the left middle temporal gyrus and inferior temporal gyrus and the cluster values of ReHo in the right precentral gyrus, superior frontal gyrus and middle frontal gyrus were strongly correlated with the CPC score (P < 0.001). There was a strong correlation between the mean ALFF and SjvO2 in CA patients (r = 0.910, P < 0.001). The SSEP N20-baseline amplitudes in CA patients were negatively correlated with thalamic rs-fMRI activity (all P < 0.001). Conclusions: This study revealed that abnormal rs-fMRI BOLD signals in resuscitated patients showed complex changes, characterized by increased activity in some local brain regions and reduced activity in others. Abnormal BOLD signals were associated with neurological outcomes in resuscitated patients. The mean ALFF values of the whole brain were closely related to SjvO2 levels, and changes in the thalamic BOLD signals correlated with the N20-baseline amplitudes of SSEP responses. Trial registration: NCT05966389 (Registered July 27, 2023). [ABSTRACT FROM AUTHOR]

Richter's transformation (RT) is a progression of chronic lymphocytic leukemia (CLL) to aggressive lymphoma. MGA (Max gene associated), a functional MYC suppressor, is mutated at 3% in CLL and 36% in RT. However, genetic models and molecular mechanisms of MGA deletion that drive CLL to RT remain elusive. We established an RT mouse model by knockout of Mga in the Sf3b1/Mdr CLL model using CRISPR-Cas9 to determine the role of Mga in RT. Murine RT cells exhibited mitochondrial aberrations with elevated oxidative phosphorylation (OXPHOS). Through RNA sequencing and functional characterization, we identified Nme1 (nucleoside diphosphate kinase) as an Mga target, which drives RT by modulating OXPHOS. Given that NME1 is also a known MYC target without targetable compounds, we found that concurrent inhibition of MYC and electron transport chain complex II substantially prolongs the survival of RT mice in vivo. Our results suggest that the Mga-Nme1 axis drives murine CLL-to-RT transition via modulating OXPHOS, highlighting a potential therapeutic avenue for RT. Editor's summary: Richter's transformation (RT) involves the progression of chronic lymphocytic leukemia (CLL) to a more aggressive lymphoma with poor outcomes. Understanding the transition into RT is key to more targeted therapeutic strategies. Iyer et al. examined the role of the MYC suppressor MGA, which is differentially expressed in RT, in an in vivo CLL model with MGA dysfunction. MGA loss resulted in increased mitochondrial function and reactive oxygen species and led to aberrant cell morphology and up-regulated MYC as commonly observed in patients. Combined inhibition of MYC and mitochondrial respiration prolonged in vivo survival in this model, highlighting potential therapeutic strategies for RT with this genetic profile. —Catherine Charneski [ABSTRACT FROM AUTHOR]

Background: Adipose tissue is significantly involved in inflammatory bowel disease (IBD). Vitamin D can affect both adipogenesis and inflammation. The aim of this study was to compare the production of selected adipokines, potentially involved in the pathogenesis of IBD - adiponectin, resistin, retinol binding protein 4 (RBP-4), adipocyte fatty acid binding protein and nesfatin-1 in children with IBD according to the presence of 25-hydroxyvitamin D (25(OH)D) deficiency. Methods: The study was conducted as a case-control study in pediatric patients with IBD and healthy children of the same sex and age. In addition to adipokines and 25(OH)D, anthropometric parameters, markers of inflammation and disease activity were assessed in all participants. Results: Children with IBD had significantly higher resistin levels regardless of 25(OH)D levels. IBD patients with 25(OH)D deficiency only had significantly lower RBP-4 compared to healthy controls and also compared to IBD patients without 25(OH)D deficiency. No other significant differences in adipokines were found in children with IBD with or without 25(OH)D deficiency. 25(OH)D levels in IBD patients corelated with RBP-4 only, and did not correlate with other adipokines. Conclusions: Whether the lower RBP-4 levels in the 25(OH)D-deficient group of IBD patients directly reflect vitamin D deficiency remains uncertain. The production of other adipokines does not appear to be directly related to vitamin D deficiency. [ABSTRACT FROM AUTHOR]

To understand the neurocognitive mechanisms that underlie heterogeneity in cognitive ageing, recent scientific efforts have led to a growing public availability of imaging cohort data. The Advanced BRain Imaging on ageing and Memory (ABRIM) project aims to add to these existing datasets by taking an adult lifespan approach to provide a cross-sectional, normative database with a particular focus on connectivity, myelinization and iron content of the brain in concurrence with cognitive functioning, mechanisms of reserve, and sleep-wake rhythms. ABRIM freely shares MRI and behavioural data from 295 participants between 18–80 years, stratified by age decade and sex (median age 52, IQR 36–66, 53.20% females). The ABRIM MRI collection consists of both the raw and pre-processed structural and functional MRI data to facilitate data usage among both expert and non-expert users. The ABRIM behavioural collection includes measures of cognitive functioning (i.e., global cognition, processing speed, executive functions, and memory), proxy measures of cognitive reserve (e.g., educational attainment, verbal intelligence, and occupational complexity), and various self-reported questionnaires (e.g., on depressive symptoms, pain, and the use of memory strategies in daily life and during a memory task). In a sub-sample (n = 120), we recorded sleep-wake rhythms using an actigraphy device (Actiwatch 2, Philips Respironics) for a period of 7 consecutive days. Here, we provide an in-depth description of our study protocol, pre-processing pipelines, and data availability. ABRIM provides a cross-sectional database on healthy participants throughout the adult lifespan, including numerous parameters relevant to improve our understanding of cognitive ageing. Therefore, ABRIM enables researchers to model the advanced imaging parameters and cognitive topologies as a function of age, identify the normal range of values of such parameters, and to further investigate the diverse mechanisms of reserve and resilience. [ABSTRACT FROM AUTHOR]

The cerebral cortex is populated by specialized regions that are organized into networks. Here we estimated networks from functional MRI (fMRI) data in intensively sampled participants. The procedure was developed in two participants (scanned 31 times) and then prospectively applied to 15 participants (scanned 8–11 times). Analysis of the networks revealed a global organization. Locally organized first-order sensory and motor networks were surrounded by spatially adjacent second-order networks that linked to distant regions. Third-order networks possessed regions distributed widely throughout association cortex. Regions of distinct third-order networks displayed side-by-side juxtapositions with a pattern that repeated across multiple cortical zones. We refer to these as supra-areal association megaclusters (SAAMs). Within each SAAM, two candidate control regions were adjacent to three separate domain-specialized regions. Response properties were explored with task data. The somatomotor and visual networks responded to body movements and visual stimulation, respectively. Second-order networks responded to transients in an oddball detection task, consistent with a role in orienting to salient events. The third-order networks, including distinct regions within each SAAM, showed two levels of functional specialization. Regions linked to candidate control networks responded to working memory load across multiple stimulus domains. The remaining regions dissociated across language, social, and spatial/episodic processing domains. These results suggest that progressively higher-order networks nest outward from primary sensory and motor cortices. Within the apex zones of association cortex, there is specialization that repeatedly divides domain-flexible from domain-specialized regions. We discuss implications of these findings, including how repeating organizational motifs may emerge during development. NEW & NOTEWORTHY: The organization of cerebral networks was estimated within individuals with intensive, repeat sampling of fMRI data. A hierarchical organization emerged in each individual that delineated first-, second-, and third-order cortical networks. Regions of distinct third-order association networks consistently exhibited side-by-side juxtapositions that repeated across multiple cortical zones, with clear and robust functional specialization among the embedded regions. [ABSTRACT FROM AUTHOR]

The default mode network (DMN) lies towards the heteromodal end of the principal gradient of intrinsic connectivity, maximally separated from the sensory‐motor cortex. It supports memory‐based cognition, including the capacity to retrieve conceptual and evaluative information from sensory inputs, and to generate meaningful states internally; however, the functional organisation of DMN that can support these distinct modes of retrieval remains unclear. We used fMRI to examine whether activation within subsystems of DMN differed as a function of retrieval demands, or the type of association to be retrieved, or both. In a picture association task, participants retrieved semantic associations that were either contextual or emotional in nature. Participants were asked to avoid generating episodic associations. In the generate phase, these associations were retrieved from a novel picture, while in the switch phase, participants retrieved a new association for the same image. Semantic context and emotion trials were associated with dissociable DMN subnetworks, indicating that a key dimension of DMN organisation relates to the type of association being accessed. The frontotemporal and medial temporal DMN showed a preference for emotional and semantic contextual associations, respectively. Relative to the generate phase, the switch phase recruited clusters closer to the heteromodal apex of the principal gradient—a cortical hierarchy separating unimodal and heteromodal regions. There were no differences in this effect between association types. Instead, memory switching was associated with a distinct subnetwork associated with controlled internal cognition. These findings delineate distinct patterns of DMN recruitment for different kinds of associations yet common responses across tasks that reflect retrieval demands. [ABSTRACT FROM AUTHOR]

The space-charge-limited-current spectroscopy is a consolidated technique for studying electrical properties of materials and devices. In general, the conduction in the material can be expressed as a single scaling law, relating the current with voltage and gap (or sample thickness) with different values for the exponents. However, some aspects of this technique remain obscure, especially when dealing with very thin (few nanometer) gaps and solids. Beyond this, abrupt transitions between different transport regimes are observed, whereas unusual space-charge-limited current behaviors are expected in out of 2D plane of 2D-material-based heterostructures. Therefore, there is a need for a universal model to describe the current–voltage characteristic curves, including different conduction mechanisms as well as smooth transitions between them. This goal, pursued for decades without substantial success, is not achievable based on the mentioned simple scaling laws, requiring a new approach. In this work, we propose a universal model with the same underlying physics. A new function is considered which contains relevant information for transport and accounts for most of the fingerprints observed in experimental current–voltage curves of the most diverse set of physical systems, from materials to devices. This approach leads to the usual scaling laws for constant values of the transport function, whereas it is abandoned for the trap filling regime, although the same familiar higher slopes of current–voltage curves can be recovered. The model is used to fit the experimental curves of the most diverse materials and devices in order to show its applicability and accuracy. [ABSTRACT FROM AUTHOR]

Dynamic susceptibility contrast (DSC) MRI plays a pivotal role in the accurate diagnosis and prognosis of several neurovascular diseases, but is limited by its reliance on gadolinium, an intravascularly injected chelated metal. Here, we determined the feasibility of measuring perfusion using a DSC analysis of breath-hold-induced gradient-echo-MRI signal changes. We acquired data at both 3 T and 7 T from ten healthy participants who engaged in eight consecutive breath-holds. By pairing a novel arterial input function strategy with a standard DSC MRI analysis, we measured the cerebral blood volume, flow, and transit delay, and found values to agree with those documented in the literature using gadolinium. We also observed voxel-wise agreement between breath-hold and arterial spin labeling measures of cerebral blood flow. Breath-holding resulted in significantly higher contrast-to-noise (6.2 at 3 T vs. 8.5 at 7 T) and gray matter-to-white matter contrast at higher field strength. Finally, using a simulation framework to assess the effect of dynamic vasodilation on perfusion estimation, we found global perfusion underestimation of 20–40%. For the first time, we have assessed the feasibility of and limitations associated with using breath-holds for perfusion estimation with DSC. We hope that the methods and results presented in this study will help pave the way toward contrast-free perfusion imaging, in both basic and clinical research. [ABSTRACT FROM AUTHOR]

Cerebrovascular Reactivity (CVR) refers to the ability of cerebral blood vessels to dilate or constrict under the effect of vasoactive substances and can be estimated using functional Magnetic Resonance Imaging (fMRI). Computation of CVR maps is relevant in various brain diseases and requires specialized data processing. We introduce CVRmap, an opensource software that automates the computation of CVR map. The toolbox complies with the Brain Imaging Data Structure (BIDS) standards. [ABSTRACT FROM AUTHOR]

Data standardization promotes a common framework through which researchers can utilize others' data and is one of the leading methods neuroimaging researchers use to share and replicate findings. As of today, standardizing datasets requires technical expertise such as coding and knowledge of file formats. We present ezBIDS, a tool for converting neuroimaging data and associated metadata to the Brain Imaging Data Structure (BIDS) standard. ezBIDS contains four major features: (1) No installation or programming requirements. (2) Handling of both imaging and task events data and metadata. (3) Semi-automated inference and guidance for adherence to BIDS. (4) Multiple data management options: download BIDS data to local system, or transfer to OpenNeuro.org or to brainlife.io. In sum, ezBIDS requires neither coding proficiency nor knowledge of BIDS, and is the first BIDS tool to offer guided standardization, support for task events conversion, and interoperability with OpenNeuro.org and brainlife.io. [ABSTRACT FROM AUTHOR]

Obesity affects more than one billion people worldwide and often leads to cardiometabolic chronic comorbidities. It induces senescence-related alterations in adipose tissue, and senescence is closely linked to obesity. Fully elucidating the pathways through which vitamin D exerts anti-inflammatory effects may improve our understanding of local adipose tissue inflammation and the pathogenesis of metabolic disorders. In this narrative review, we compiled and analyzed the literature from diverse academic sources, focusing on recent developments to provide a comprehensive overview of the effect of vitamin D on inflammation associated with obesity and senescence. The article reveals that the activation of the NF-κB (nuclear factor kappa B subunit 1) and NLRP3 inflammasome (nucleotide-binding domain, leucine-rich-containing, pyrin domain-containing-3) pathways through the toll-like receptors, which increases oxidative stress and cytokine release, is a common mechanism underlying inflammation associated with obesity and senescence, and it discusses the potential beneficial effect of vitamin D in alleviating the development of subclinical inflammation. Investigating the main target cells and pathways of vitamin D action in adipose tissue could help uncover complex mechanisms of obesity and cellular senescence. This review summarizes significant findings related to opportunities for improving metabolic health. [ABSTRACT FROM AUTHOR]

Affective neuroscience has traditionally relied on cross-sectional studies to uncover the brain correlates of affects, emotions, and moods. Such findings obfuscate intraindividual variability that may reveal meaningful changing affect states. The few functional magnetic resonance imaging longitudinal studies that have linked changes in brain function to the ebbs and flows of affective states over time have mostly investigated a single individual. In this study, we explored how the functional connectivity of brain areas associated with affective processes can explain within-person fluctuations in self-reported positive and negative affects across several subjects. To do so, we leveraged the Day2day dataset that includes 40 to 50 resting-state functional magnetic resonance imaging scans along self-reported positive and negative affectivity from a sample of six healthy participants. Sparse multivariate mixed-effect linear models could explain 15% and 11% of the within-person variation in positive and negative affective states, respectively. Evaluation of these models' generalizability to new data demonstrated the ability to predict approximately 5% and 2% of positive and negative affect variation. The functional connectivity of limbic areas, such as the amygdala, hippocampus, and insula, appeared most important to explain the temporal dynamics of affects over days, weeks, and months., (© 2024. The Author(s).)

Purpose: To investigate longitudinal associations between the vitamin D status and inflammatory markers in children and adolescents., Methods: Children from eight European countries from the IDEFICS/I.Family cohort with repeated measurements were included in this study. A linear mixed-effect model was used to model the association of serum 25(OH)D as independent variable and z-scores of inflammatory markers [CRP, cytokines, adipokines, combined inflammation score] as dependent variables, where one level accounts for differences between individuals and the other for changes over age within individuals., Results: A total of 1,582 children were included in the study. In the adjusted model, 25(OH)D levels were positively associated with adiponectin (β = 0.11 [95% CI 0.07; 0.16]) and negatively with the inflammation score (β = - 0.24 [95% CI - 0.40; - 0.08]) indicating that the adiponectin z-score increased by 0.11 units and the inflammation score decreased by 0.24 units per 12.5 nmol/l increase in 25(OH)D. In children with overweight or obesity, only a positive association between 25(OH)D and IP-10 was observed while in children with normal weight adiponectin was positively and the inflammation score was negatively associated. Associations of vitamin D with adiponectin and the inflammation score were stronger in girls than in boys and a positive association with TNF-α was observed only in girls., Conclusion: Our results suggest that an increase in vitamin D concentrations may help to regulate inflammatory biomarkers. However, it seems to be no benefit of a better vitamin D status in children with overweight/obesity unless their weight is managed to achieve an improved inflammatory marker status., (© 2024. The Author(s).)

Objectives: Subclinical hypothyroidism (SH) is defined by normal free triiodothyronine (fT3) and free thyroxine (fT4) levels, elevated thyroid-stimulating hormone levels, and the absence of overt clinical signs of hypothyroidism. The natural course of SH is influenced by the underlying etiology. The purpose of this study was to evaluate the etiologic causes of SH., Methods: A total of 135 patients aged 1-18 years, diagnosed with SH by at least two analytical measurements, were included in the study. The anthropometric measurements, demographic characteristics, and laboratory findings of the patients were determined. A comparison was conducted between patients with Hashimoto's thyroiditis and patients with non-autoimmune etiology., Results: The median age was 9.7 (6.5) years, and 82 of the 135 patients were female. The most prevalent etiology was idiopathic, affecting 39 (28.9 %) patients. This was followed by obesity, which was identified in 21 (15.6 %) patients. Hashimoto's thyroiditis was the third most common cause, accounting for 18 (13.3 %) patients. In patients with Hashimoto's disease, fT4 levels were significantly lower, and the rate of initiation of LT4 treatment was higher than in patients with other etiologies. A heterozygous variation in the TSH receptor (TSHR) gene was detected in six patients., Conclusions: In our study, idiopathic cases were the most frequently identified in the etiology of SH. It is important to determine whether there is autoimmune thyroiditis. In cases of idiopathic SH, it is recommended to perform TSHR gene analysis, particularly in the presence of positive family history and newborn screening results. This approach will help elucidate the underlying etiology., (© 2024 Walter de Gruyter GmbH, Berlin/Boston.)

The Latin American Brain Health Institute (BrainLat) has released a unique multimodal neuroimaging dataset of 780 participants from Latin American. The dataset includes 530 patients with neurodegenerative diseases such as Alzheimer's disease (AD), behavioral variant frontotemporal dementia (bvFTD), multiple sclerosis (MS), Parkinson's disease (PD), and 250 healthy controls (HCs). This dataset (62.7 ± 9.5 years, age range 21–89 years) was collected through a multicentric effort across five Latin American countries to address the need for affordable, scalable, and available biomarkers in regions with larger inequities. The BrainLat is the first regional collection of clinical and cognitive assessments, anatomical magnetic resonance imaging (MRI), resting-state functional MRI (fMRI), diffusion-weighted MRI (DWI), and high density resting-state electroencephalography (EEG) in dementia patients. In addition, it includes demographic information about harmonized recruitment and assessment protocols. The dataset is publicly available to encourage further research and development of tools and health applications for neurodegeneration based on multimodal neuroimaging, promoting the assessment of regional variability and inclusion of underrepresented participants in research. [ABSTRACT FROM AUTHOR]

Obesity is a public health crisis, presenting a huge burden on health care and the economic system in both developed and developing countries. According to the WHO’s latest report on obesity, 39% of adults of age 18 and above are obese, with an increase of 18% compared to the last few decades. Metabolic energy imbalance due to contemporary lifestyle, changes in gut microbiota, hormonal imbalance, inherent genetics, and epigenetics is a major contributory factor to this crisis. Multiple studies have shown that probiotics and their metabolites (postbiotics) supplementation have an effect on obesity-related effects in vitro, in vivo, and in human clinical investigations. Postbiotics such as the SCFAs suppress obesity by regulating metabolic hormones such as GLP-1, and PPY thus reducing feed intake and suppressing appetite. Furthermore, muramyl di-peptides, bacteriocins, and LPS have been tested against obesity and yielded promising results in both human and mice studies. These insights provide an overview of targetable pharmacological sites and explore new opportunities for the safer use of postbiotics against obesity in the future. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) materials formed by thin-films of metal oxides that grow on metal supports are commonly used in heterogeneous catalysis and multilayer electronic devices. Despite extensive research on these systems, the effects of charged defects at supported oxides on surface processes are still not clear. In this work, we perform spin-polarized density-functional theory (DFT) calculations to investigate formation and interaction of charged magnesium and oxygen vacancies, and Al dopants on MgO(001)/Ag(001) surface. The results show a sizable interface compressive effect that decreases the metal work function as electrons are added on the MgO surface with a magnesium vacancy. This surface displays a larger formation energy in a water environment (O-rich condition) even with additional Al-doping. Under these conditions, we found that a polar molecule such as CO is more strongly adsorbed on the low-coordination oxygen sites due to a larger contribution of the channeled electronic transport with the silver interface regardless of the surface charge. Therefore, these findings elucidate how surface intrinsic vacancies can influence or contribute to charge transfer, which allows one to explore more specific reactions at different surface topologies for more efficient catalysts for CO2 conversion. [ABSTRACT FROM AUTHOR]

The BIDSconvertR package is the first R-based tool for organizing magnetic resonance imaging (MRI) research data in accordance with the Brain Imaging Data Structure (BIDS) specification. Key features are the DICOM (Digital Imaging and Communications in Medicine) to NIfTI (Neuroimaging Informatics Technology Initiative) and NIfTI to BIDS conversion, the implementation of the BIDS Validator and a MRI data viewer to efficiently manage MRI neuroimaging data sets. The BIDSconvertR offers an interactive user dialogue and a graphical user interface. BIDS validation is facilitated by color-coding of the BIDS sequence-IDs. Data cleaning is simplified by the option of using regular expressions. The BIDSconvertR contributes to the growing efforts to improve reproducibility in neuroimaging research by facilitating researchers to share and organize data in a standardized and transparent manner. [ABSTRACT FROM AUTHOR]

Various evidences have unveiled the significance of Vitamin D in diverse processes which include its action in prevention of immune dysfunction, cancer and cardiometabolic disorders. Studies have confirmed the function of VD in controlling the expression of approximately nine hundred genes including gene expression of insulin. VD insufficiency may be linked with the pathogenesis of diseases that are associated with insulin resistance (IR) including diabetes as well as obesity. Thus, VD lowers IR-related disorders such as inflammation and oxidative stress. This review provides an insight regarding the molecular mechanism manifesting, how insufficiency of VD may be connected with the IR and diabetes. It also discusses the effect of VD in maintaining the Ca2+ levels in beta cells of the pancreas and in the tissues that are responsive to insulin. [ABSTRACT FROM AUTHOR]

Understanding the kinetic competition between charge extraction and recombination, and how this is impacted by mobile ions, remains a key challenge in perovskite solar cells (PSCs). Here, this issue is addressed by combining operando photoluminescence (PL) measurements, which allow the measurement of real‐time PL spectra during current–voltage (J–V) scans under 1‐sun equivalent illumination, with the results of drift‐diffusion simulations. This operando PL analysis allows direct comparison between the internal performance (recombination currents and quasi‐Fermi‐level‐splitting (QFLS)) and the external performance (J–V) of a PSC during operation. Analyses of four PSCs with different electron transport materials (ETMs) quantify how a deeper ETM LUMO induces greater interfacial recombination, while a shallower LUMO impedes charge extraction. Furthermore, it is found that a low ETM mobility leads to charge accumulation in the perovskite under short‐circuit conditions. However, thisalone cannot explain the remarkably high short‐circuit QFLS of over 1 eV which is observed in all devices. Instead, drift‐diffusion simulations allow this effect to be assigned to the presence of mobile ions which screen the internal electric field at short‐circuit and lead to a reduction in the short‐circuit current density by over 2 mA cm−2 in the best device. [ABSTRACT FROM AUTHOR]

Selecting suitable charge transport layers and suppressing non‐radiative recombination at interfaces with the absorber layer is vital for maximizing the efficiency of halide perovskite solar cells. In this study, high‐quality perovskite thin films and devices are fabricated with different fullerene‐based electron transport layers and different self‐assembled monolayers as hole transport layers. Then, a comparative study of a significant variety of different electrical, optical, and photoemission‐based characterization techniques is performed to quantify the properties of the solar cells, individual layers, and, importantly, the interfaces between them. In addition, the limitations and problems of the different measurements, the insights gained by combining different methods, and the different strategies for extracting information from the experimental raw data, are highlighted. [ABSTRACT FROM AUTHOR]

Background: Polycystic ovary syndrome (PCOS) is an endocrine disorder with disrupted uterus structure and function. A positive effect of vitamin D3 (VD3) in female reproduction was observed. Chemerin (RARRES2) and adiponectin (ADIPOQ) are the main adipokines whose levels are altered in PCOS patients. Therefore, the aim of this study was to investigate the impact of VD3 supplementation on RARRES2 and ADIPOQ levels in the uterus of PCOS rats. Methods: We analyzed the plasma levels and uterine transcript and protein expression of RARRES2 and ADIPOQ and their receptors (CCRL2, CMKLR1, GPR1, and ADIPOR1 and ADIPOR2, respectively) in rats with letrozole-induced PCOS. Results: In control animals, VD3 did not change plasma levels of both adipokines, while in PCOS rats supplemented with VD3, they returned to control levels. The expression of RARRES2 and all investigated receptors increased in the uterus of VD3-treated rats; however, the levels of Rarres2 and Gpr1 genes remained unchanged. VD3 supplementation decreased RARRES2, CMKLR1, and GPR1 but increased CCRL2 level to the control value. In the uterus of VD3-treated rats, the transcript and protein levels of ADIPOQ and both receptors ADIPOR1 increased. At the same time, VD3 supplementation induced an increase in Adipoq, Adipor1, and Adipor2 gene expression and restored protein levels to control level values. Conclusions: our findings indicate a new mechanism of VD3 action in the uterine physiology of PCOS rats. [ABSTRACT FROM AUTHOR]

The presence of crystallographic defects can induce notable effects on the mechanisms ruling the current transport in metal/semiconductor contacts. In this context, in this Letter, the impact of stacking faults (SFs) on the characteristics of 4H-SiC Schottky diodes was investigated under both forward and reverse bias. In particular, in the presence of SFs under the contact, while no significant effect on the ideality factor and barrier height was observed under forward bias, an anomalous increase in the leakage current occurred under reverse bias. The observed behavior of the leakage current could be explained by a space-charge limited current model, consistent with the presence of a distribution of trapping states in the gap of 4H-SiC. An increase in the reverse bias above 30 V leads to a complete trap filling. The weak temperature-dependence of the leakage current observed in this regime suggests the coexistence with a tunneling of the carriers through the barrier. The results can be useful to understand unexpected failures in 4H-SiC Schottky diodes. [ABSTRACT FROM AUTHOR]

To fluidly engage with the world, our brains must simultaneously represent both the scene in front of us and our memory of the immediate surrounding environment (i.e., local visuospatial context). How does the brain's functional architecture enable sensory and mnemonic representations to closely interface while also avoiding sensory-mnemonic interference? Here, we asked this question using first-person, head-mounted virtual reality and fMRI. Using virtual reality, human participants of both sexes learned a set of immersive, real-world visuospatial environments in which we systematically manipulated the extent of visuospatial context associated with a scene image in memory across three learning conditions, spanning from a single FOV to a city street. We used individualized, within-subject fMRI to determine which brain areas support memory of the visuospatial context associated with a scene during recall (Experiment 1) and recognition (Experiment 2). Across the whole brain, activity in three patches of cortex was modulated by the amount of known visuospatial context, each located immediately anterior to one of the three scene perception areas of high-level visual cortex. Individual subject analyses revealed that these anterior patches corresponded to three functionally defined place memory areas, which selectively respond when visually recalling personally familiar places. In addition to showing activity levels that were modulated by the amount of visuospatial context, multivariate analyses showed that these anterior areas represented the identity of the specific environment being recalled. Together, these results suggest a convergence zone for scene perception and memory of the local visuospatial context at the anterior edge of high-level visual cortex. [ABSTRACT FROM AUTHOR]

Magnetic resonance imaging of the brain is a useful tool in both the clinic and research settings, aiding in the diagnosis and treatments of neurological disease and expanding our knowledge of the brain. However, there are many challenges inherent in managing and analyzing MRI data, due in large part to the heterogeneity of data acquisition. To address this, we have developed MRIO, the Magnetic Resonance Imaging Acquisition and Analysis Ontology. MRIO provides well-reasoned classes and logical axioms for the acquisition of several MRI acquisition types and well-known, peer-reviewed analysis software, facilitating the use of MRI data. These classes provide a common language for the neuroimaging research process and help standardize the organization and analysis of MRI data for reproducible datasets. We also provide queries for automated assignment of analyses for given MRI types. MRIO aids researchers in managing neuroimaging studies by helping organize and annotate MRI data and integrating with existing standards such as Digital Imaging and Communications in Medicine and the Brain Imaging Data Structure, enhancing reproducibility and interoperability. MRIO was constructed according to Open Biomedical Ontologies Foundry principles and has contributed several classes to the Ontology for Biomedical Investigations to help bridge neuroimaging data to other domains. MRIO addresses the need for a "common language" for MRI that can help manage the neuroimaging research, by enabling researchers to identify appropriate analyses for sets of scans and facilitating data organization and reporting., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The increasing use of neuroimaging in clinical research has driven the creation of many large imaging datasets. However, these datasets often rely on inconsistent naming conventions in image file headers to describe acquisition, and time-consuming manual curation is necessary. Therefore, we sought to automate the process of classifying and organizing magnetic resonance imaging (MRI) data according to acquisition types common to the clinical routine, as well as automate the transformation of raw, unstructured images into Brain Imaging Data Structure (BIDS) datasets. To do this, we trained an XGBoost model to classify MRI acquisition types using relatively few acquisition parameters that are automatically stored by the MRI scanner in image file metadata, which are then mapped to the naming conventions prescribed by BIDS to transform the input images to the BIDS structure. The model recognizes MRI types with 99.475% accuracy, as well as a micro/macro-averaged precision of 0.9995/0.994, a micro/macro-averaged recall of 0.9995/0.989, and a micro/macro-averaged F1 of 0.9995/0.991. Our approach accurately and quickly classifies MRI types and transforms unstructured data into standardized structures with little-to-no user intervention, reducing the barrier of entry for clinical scientists and increasing the accessibility of existing neuroimaging data., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

NeuroHackademy ( https://neurohackademy.org ) is a two-week event designed to train early-career neuroscience researchers in data science methods and their application to neuroimaging. The event seeks to bridge the big data skills gap by introducing participants to data science methods and skills that are often ignored in traditional curricula. Such skills are needed for the analysis and interpretation of the kinds of large and complex datasets that have become increasingly important to neuroimaging research due to concerted data collection efforts. In 2020, the event rapidly pivoted from an in-person event to an online event that included hundreds of participants from all over the world. This experience and those of the participants substantially changed our valuation of large online-accessible events. In subsequent events held in 2022 and 2023, we have developed a "hybrid" format that includes both online and in-person participants. We discuss the technical and sociotechnical elements of hybrid events and discuss some of the lessons we have learned while organizing them. We emphasize in particular the role that these events can play in creating a global and inclusive community of practice in the intersection of neuroimaging and data science., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Neuroimaging research requires purpose-built analysis software, which is challenging to install and may produce different results across computing environments. The community-oriented, open-source Neurodesk platform ( https://www.neurodesk.org/ ) harnesses a comprehensive and growing suite of neuroimaging software containers. Neurodesk includes a browser-accessible virtual desktop, command-line interface and computational notebook compatibility, allowing for accessible, flexible, portable and fully reproducible neuroimaging analysis on personal workstations, high-performance computers and the cloud., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Background: Human growth hormone (hGH) plays a crucial role in growth by binding to growth hormone receptor (GHR) in target cells. Binding of GH molecules to their cognate receptors triggers downstream signaling pathways leading to the transcription of several genes, including insulin-like growth factor (IGF)-1. Pathogenic variants in the GHR gene can result in structural and functional defects in the GHR protein, leading to Laron Syndrome (LS) with the primary clinical manifestation of short stature. So far, around 100 GHR variants have been reported, mostly biallelic, as causing LS. Case presentation: We report on three siblings from an Iranian consanguineous family who presented with dwarfism. Whole-exome sequencing (WES) was performed on the proband, revealing a novel homozygous missense variant in the GHR gene (NM_000163.5; c.610 T > A, p.(Trp204Arg)) classified as a likely pathogenic variant according to the recommendation of the American College of Medical Genetics (ACMG). Co-segregation analysis was investigated using Sanger sequencing. Conclusions: To date, approximately 400–500 LS cases with GHR biallelic variants, out of them 10 patients originating from Iran, have been described in the literature. Given the high rate of consanguineous marriages in the Iranian population, the frequency of LS is expected to be higher, which might be explained by undiagnosed cases. Early diagnosis of LS is very important, as treatment is available for this condition. [ABSTRACT FROM AUTHOR]

Efficient electron injection from an electrode into an organic semiconductor remains a problem to solve for efficient organic semiconductor devices. In this work, a general method is presented to form an ohmic electron contact by inserting a thin organic interlayer between the metal electrode and the organic semiconductor. It is demonstrated that inserting an interlayer of a few nanometers of an organic semiconductor with a lower electron affinity than the transport material can improve the injected electron current by over three orders of magnitude. The electron current becomes space‐charge limited, demonstrating that the interlayer‐enhanced contact is ohmic. The ohmic‐contact formation by inserting a thin interlayer is ascribed to the elimination of barrier formation as a result of direct contact between the metal and organic semiconductor. Additionally, it is demonstrated that it is possible to achieve solution processing of such interlayers on top of organic semiconductors. The method is generalized for different interlayer materials as well as for different organic semiconductors, providing a general method for ohmic electron injection in organic devices. [ABSTRACT FROM AUTHOR]

Magnetic resonance spectroscopy (MRS) can non-invasively measure levels of endogenous metabolites in living tissue and is of great interest to neuroscience and clinical research. To this day, MRS data analysis workflows differ substantially between groups, frequently requiring many manual steps to be performed on individual datasets, e.g., data renaming/sorting, manual execution of analysis scripts, and manual assessment of success/failure. Manual analysis practices are a substantial barrier to wider uptake of MRS. They also increase the likelihood of human error and prevent deployment of MRS at large scale. Here, we demonstrate an end-to-end workflow for fully automated data uptake, processing, and quality review. The proposed continuous automated MRS analysis workflow integrates several recent innovations in MRS data and file storage conventions. They are efficiently deployed by a directory monitoring service that automatically triggers the following steps upon arrival of a new raw MRS dataset in a project folder: (1) conversion from proprietary manufacturer file formats into the universal format NIfTI-MRS; (2) consistent file system organization according to the data accumulation logic standard BIDS-MRS; (3) executing a command-line executable of our open-source end-to-end analysis software Osprey; (4) e-mail delivery of a quality control summary report for all analysis steps. The automated architecture successfully completed for a demonstration dataset. The only manual step required was to copy a raw data folder into a monitored directory. Continuous automated analysis of MRS data can reduce the burden of manual data analysis and quality control, particularly for non-expert users and multi-center or large-scale studies and offers considerable economic advantages. [ABSTRACT FROM AUTHOR]

Simple Summary: Cats with chronic kidney disease (CKD) frequently suffer from weight loss and inadequate caloric intake due to poor appetite. Ghrelin is a key hormone involved in the regulation of appetite, and it circulates in two forms: acylated and desacyl ghrelin. Acylated ghrelin is associated with initiating and stimulating appetite, whereas desacyl ghrelin is considered anorexigenic. To investigate appetite regulation in cats, this study compared plasma acylated, total, and calculated desacyl ghrelin concentrations in cats with and without CKD. The results demonstrate that cats with CKD have increased desacyl and total ghrelin concentrations in comparison to normal cats, consistent with dysregulation of appetite. This increase was correlated with disease severity. Appetite abnormalities and weight loss are important comorbidities in the treatment of chronic kidney disease (CKD) in cats. Ghrelin, a key hormone involved in the regulation of appetite and metabolism, is a potential marker of appetite dysregulation in cats with CKD. The aim of this study was to compare the plasma concentrations of acylated, desacyl, and total ghrelin in normal cats and cats with CKD. Storage methodology was investigated prior to evaluating ghrelin concentrations in normal and CKD cats to facilitate clinical sample collection. Twelve normal cats and twelve cats with CKD were enrolled. Plasma acylated and total ghrelin concentrations were measured using radioimmunoassay. Desacyl ghrelin was calculated (total ghrelin minus acylated ghrelin). Cats with CKD had significantly increased total ghrelin and calculated desacyl ghrelin concentrations in comparison to normal cats (p < 0.0001 and p = 0.0001). There was no significant difference in active ghrelin concentrations between groups. Both total ghrelin and calculated desacyl ghrelin were significantly correlated with serum creatinine concentrations (p < 0.0001, r = 0.70 and p < 0.0001, r = 0.73). Elevated plasma desacyl ghrelin concentrations in cats with CKD provides evidence for dysregulation of appetite in feline CKD. [ABSTRACT FROM AUTHOR]

Cerebrovascular disease is a leading cause of death globally. Prevention and early intervention are known to be the most effective forms of its management. Non-invasive imaging methods hold great promises for early stratification, but at present lack the sensitivity for personalized prognosis. Resting-state functional magnetic resonance imaging (rs-fMRI), a powerful tool previously used for mapping neural activity, is available in most hospitals. Here we show that rs-fMRI can be used to map cerebral hemodynamic function and delineate impairment. By exploiting time variations in breathing pattern during rs-fMRI, deep learning enables reproducible mapping of cerebrovascular reactivity (CVR) and bolus arrival time (BAT) of the human brain using resting-state CO2 fluctuations as a natural "contrast media". The deep-learning network is trained with CVR and BAT maps obtained with a reference method of CO2-inhalation MRI, which includes data from young and older healthy subjects and patients with Moyamoya disease and brain tumors. We demonstrate the performance of deep-learning cerebrovascular mapping in the detection of vascular abnormalities, evaluation of revascularization effects, and vascular alterations in normal aging. In addition, cerebrovascular maps obtained with the proposed method exhibit excellent reproducibility in both healthy volunteers and stroke patients. Deep-learning resting-state vascular imaging has the potential to become a useful tool in clinical cerebrovascular imaging. [ABSTRACT FROM AUTHOR]

A ternary strategy has been demonstrated as being an effective method to improve the power conversion efficiency (PCE); however, general rules for materials selection are not fully comprehended. Herein, nonfullerene acceptor ITIC‐M and fullerene acceptor PC70BM possessing higher lowest unoccupied molecular orbital (LUMO) and good miscibility with nonfullerene acceptor Y7 are incorporated as third components in the state‐of‐the‐art of PM6:Y7 binary blend. As a result, the device PCE for both ternary devices improves from 16.46% for binary host to 17.73% and 17.67% for ITIC‐M‐ and PC70BM‐based ternary devices, respectively. The higher LUMO of the guest acceptor can play multiple roles to elevate the open‐circuit voltage such as reducing energy‐loss and reverse saturation current, creating less‐localized shallow trap sites along with suppressing charge recombination, and decreasing Urbach energy. Moreover, the good miscibility facilitates an alloy‐like phase in acceptors domain for efficient exciton dissociation and electron transport, which leads to improved short‐circuit current density and fill factor in ternary devices. The results provide a promising approach to realize high‐performance ternary organic solar cells by synergizing the compatible third component with host acceptor. [ABSTRACT FROM AUTHOR]

BOLD sensitivity to baseline perfusion and blood volume is a well-acknowledged fMRI confound. Vascular correction techniques based on cerebrovascular reactivity (CVR) might reduce variance due to baseline cerebral blood volume, however this is predicated on an invariant linear relationship between CVR and BOLD signal magnitude. Cognitive paradigms have relatively low signal, high variance and involve spatially heterogenous cortical regions; it is therefore unclear whether the BOLD response magnitude to complex paradigms can be predicted by CVR. The feasibility of predicting BOLD signal magnitude from CVR was explored in the present work across two experiments using different CVR approaches. The first utilized a large database containing breath-hold BOLD responses and 3 different cognitive tasks. The second experiment, in an independent sample, calculated CVR using the delivery of a fixed concentration of carbon dioxide and a different cognitive task. An atlas-based regression approach was implemented for both experiments to evaluate the shared variance between task-invoked BOLD responses and CVR across the cerebral cortex. Both experiments found significant relationships between CVR and task-based BOLD magnitude, with activation in the right cuneus (R² = 0.64) and paracentral gyrus (R² = 0.71), and the left pars opercularis (R² = 0.67), superior frontal gyrus (R² = 0.62) and inferior parietal cortex (R² = 0.63) strongly predicted by CVR. The parietal regions bilaterally were highly consistent, with linear regressions significant in these regions for all four tasks. Group analyses showed that CVR correction increased BOLD sensitivity. Overall, this work suggests that BOLD signal response magnitudes to cognitive tasks are predicted by CVR across different regions of the cerebral cortex, providing support for the use of correction based on baseline vascular physiology. [ABSTRACT FROM AUTHOR]

Defect engineering in valence change memories aimed at tuning the concentration and transport of oxygen vacancies are studied extensively, however mostly focusing on contribution from individual extended defects such as single dislocations and grain boundaries. In this work, the impact of engineering large numbers of grain boundaries on resistive switching mechanisms and performances is investigated. Three different grain morphologies, that is, "random network," "columnar scaffold," and "island‐like," are realized in CeO2 thin films. The devices with the three grain morphologies demonstrate vastly different resistive switching behaviors. The best overall resistive switching performance is shown in the devices with "columnar scaffold" morphology, where the vertical grain boundaries extending through the film facilitate the generation of oxygen vacancies as well as their migration under external bias. The observation of both interfacial and filamentary switching modes only in the devices with a "columnar scaffold" morphology further confirms the contribution from grain boundaries. In contrast, the "random network" or "island‐like" structures result in excessive or insufficient oxygen vacancy concentration migration paths. The research provides design guidelines for grain boundary engineering of oxide‐based resistive switching materials to tune the resistive switching performances for memory and neuromorphic computing applications. [ABSTRACT FROM AUTHOR]

In blood-oxygen-level-dependent (BOLD)-based resting-state functional (RS-fMRI) studies, usage of multi-echo echo-planar-imaging (ME-EPI) is limited due to unacceptable late echo times when high spatial resolution is used. Equipped with high-performance gradients, the compact 3T MRI system (C3T) enables a three-echo whole-brain ME-EPI protocol with smaller than 2.5 mm isotropic voxel and shorter than 1 s repetition time, as required in landmark fMRI studies. The performance of the ME-EPI was comprehensively evaluated with signal variance reduction and region-of-interest-, seed- and independent-component-analysis-based functional connectivity analyses and compared with a counterpart of single-echo EPI with the shortest TR possible. Through the multi-echo combination, the thermal noise level is reduced. Functional connectivity, as well as signal intensity, are recovered in the medial orbital sulcus and anterior transverse collateral sulcus in ME-EPI. It is demonstrated that ME-EPI provides superior sensitivity and accuracy for detecting functional connectivity and/or brain networks in comparison with single-echo EPI. In conclusion, the high-performance gradient enabled high-spatial-temporal resolution ME-EPI would be the method of choice for RS-fMRI study on the C3T. [ABSTRACT FROM AUTHOR]

Vertical transistors are an enabler for future high-density, low-power, and high-speed electronics. However, there is still limited knowledge on these unconventional devices, resulting in a lack of rational design rules. This article clarifies the physical and electrical mechanisms of vertical organic permeable-base transistors. Unique structural features of these devices are unveiled by reproducing the switching characteristics of a fabricated high-performance fullerene transistor. The origin of base-induced current saturation is illustrated by a bias-dependent carrier and field distribution inside a semiconductor film. A series of predictive simulations are carried out based on the accumulated insights, laying a foundation for theoretically guided materials and device engineering. [ABSTRACT FROM AUTHOR]

In this work, a perylene bisimide (PBI) based electrolyte PDIN-TEMPO pendent with a stable radical 2,2,6,6-tetramethylpiperidine 1-oxyl (TEMPO) has been synthesized and used as a cathode interlayer (CIL) in organic solar cells (OSCs). The aligned energy levels of PBI and electron-conducting nature of TEMPO enabled the new CIL to show excellent performance in OSCs, displaying not only high power conversion efficiencies (PCEs) of 18.48–15.86% and high fill factors (FFs) over 0.80 with the CIL thickness in the range of 5 nm–100 nm, but also high stability and the desired generality to be used in both regular and inverted OSCs. Two controlled conjugated electrolytes by removing TEMPO or PBI units were synthesized and used as a CIL in OSCs, but their FFs were reduced based on thick CILs. Therefore, the synergism of integrated PBI and TEMPO units into one material is critical for the superior performance of PDIN-TEMPO, which was confirmed by its high conductivity and thickness-insensitive electron mobilities in OSCs. This work demonstrates that the TEMPO radical is a promising unit to design semiconducting materials for high performance OSCs. [ABSTRACT FROM AUTHOR]