In vivo whole-cortex marker of excitation-inhibition ratio indexes cortical maturation and cognitive ability in youth.

A balanced excitation-inhibition ratio (E/I ratio) is critical for healthy brain function. Normative development of cortex-wide E/I ratio remains unknown. Here, we noninvasively estimate a putative marker of whole-cortex E/I ratio by fitting a large-scale biophysically plausible circuit model to resting-state functional MRI (fMRI) data. We first confirm that our model generates realistic brain dynamics in the Human Connectome Project. Next, we show that the estimated E/I ratio marker is sensitive to the gamma-aminobutyric acid (GABA) agonist benzodiazepine alprazolam during fMRI. Alprazolam-induced E/I changes are spatially consistent with positron emission tomography measurement of benzodiazepine receptor density. We then investigate the relationship between the E/I ratio marker and neurodevelopment. We find that the E/I ratio marker declines heterogeneously across the cerebral cortex during youth, with the greatest reduction occurring in sensorimotor systems relative to association systems. Importantly, among children with the same chronological age, a lower E/I ratio marker (especially in the association cortex) is linked to better cognitive performance. This result is replicated across North American (8.2 to 23.0 y old) and Asian (7.2 to 7.9 y old) cohorts, suggesting that a more mature E/I ratio indexes improved cognition during normative development. Overall, our findings open the door to studying how disrupted E/I trajectories may lead to cognitive dysfunction in psychopathology that emerges during youth.

Forced LMX1A expression induces dorsal neural fates and disrupts patterning of human embryonic stem cells into ventral midbrain dopaminergic neurons.

The differentiation of human pluripotent stem cells into ventral mesencephalic dopaminergic (DA) fate is relevant for the treatment of Parkinson's disease. Shortcuts to obtaining DA cells through direct reprogramming often include forced expression of the transcription factor LMX1A. Although reprogramming with LMX1A can generate tyrosine hydroxylase (TH)-positive cells, their regional identity remains elusive. Using an in vitro model of early human neural tube patterning, we report that forced LMX1A expression induced a ventral-to-dorsal fate shift along the entire neuroaxis with the emergence of roof plate fates despite the presence of ventralizing molecules. The LMX1A-expressing progenitors gave rise to grafts containing roof plate-derived choroid plexus cysts as well as ectopically induced TH-positive neurons of a forebrain identity. Early activation of LMX1A prior to floor plate specification was necessary for the dorsalizing effect. Our work suggests using caution in employing LMX1A for the induction of DA fate, as this factor may generate roof plate rather than midbrain fates.

pNet: A toolbox for personalized functional networks modeling.

Personalized functional networks (FNs) derived from functional magnetic resonance imaging (fMRI) data are useful for characterizing individual variations in the brain functional topography associated with the brain development, aging, and disorders. To facilitate applications of the personalized FNs with enhanced reliability and reproducibility, we develop an open-source toolbox that is user-friendly, extendable, and includes rigorous quality control (QC), featuring multiple user interfaces (graphics, command line, and a step-by-step guideline) and job-scheduling for high performance computing (HPC) clusters. Particularly, the toolbox, named personalized functional network modeling (pNet), takes fMRI inputs in either volumetric or surface type, ensuring compatibility with multiple fMRI data formats, and computes personalized FNs using two distinct modeling methods: one method optimizes the functional coherence of FNs, while the other enhances their independence. Additionally, the toolbox provides HTML-based reports for QC and visualization of personalized FNs. The toolbox is developed in both MATLAB and Python platforms with a modular design to facilitate extension and modification by users familiar with either programming language. We have evaluated the toolbox on two fMRI datasets and demonstrated its effectiveness and user-friendliness with interactive and scripting examples. pNet is publicly available at https://github.com/MLDataAnalytics/pNet.

In-vivo whole-cortex marker of excitation-inhibition ratio indexes cortical maturation and cognitive ability in youth.

A balanced excitation-inhibition ratio (E/I ratio) is critical for healthy brain function. Normative development of cortex-wide E/I ratio remains unknown. Here we non-invasively estimate a putative marker of whole-cortex E/I ratio by fitting a large-scale biophysically-plausible circuit model to resting-state functional MRI (fMRI) data. We first confirm that our model generates realistic brain dynamics in the Human Connectome Project. Next, we show that the estimated E/I ratio marker is sensitive to the GABA-agonist benzodiazepine alprazolam during fMRI. Alprazolam-induced E/I changes are spatially consistent with positron emission tomography measurement of benzodiazepine receptor density. We then investigate the relationship between the E/I ratio marker and neurodevelopment. We find that the E/I ratio marker declines heterogeneously across the cerebral cortex during youth, with the greatest reduction occurring in sensorimotor systems relative to association systems. Importantly, among children with the same chronological age, a lower E/I ratio marker (especially in association cortex) is linked to better cognitive performance. This result is replicated across North American (8.2 to 23.0 years old) and Asian (7.2 to 7.9 years old) cohorts, suggesting that a more mature E/I ratio indexes improved cognition during normative development. Overall, our findings open the door to studying how disrupted E/I trajectories may lead to cognitive dysfunction in psychopathology that emerges during youth.

Interarm Blood Pressure Difference Revealing a Right-Sided Aortic Arch and Occluded Aberrant Left Subclavian Artery.

We present the case of a 33-year-old patient with a rare combination of a right-sided aortic arch and occluded asymptomatic aberrant left subclavian artery diagnosed after the coincidental finding of an interarm blood pressure difference. Because there were no symptoms of local compression or subclavian steal, conservative management was suggested.

Validation of the structured interview section of the penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT GOASSESS).

Large-scale studies and burdened clinical settings require precise, efficient measures that assess multiple domains of psychopathology. Computerized adaptive tests (CATs) can reduce administration time without compromising data quality. We examined feasibility and validity of an adaptive psychopathology measure, GOASSESS, in a clinical community-based sample (N = 315; ages 18-35) comprising three groups: healthy controls, psychosis, mood/anxiety disorders. Assessment duration was compared between the Full and CAT GOASSESS. External validity was tested by comparing how the CAT and Full versions related to demographic variables, study group, and socioeconomic status. The relationships between scale scores and criteria were statistically compared within a mixed-model framework to account for dependency between relationships. Convergent validity was assessed by comparing scores of the CAT and the Full GOASSESS using Pearson correlations. The CAT GOASSESS reduced interview duration by more than 90 % across study groups and preserved relationships to external criteria and demographic variables as the Full GOASSESS. All CAT GOASSESS scales could replace those of the Full instrument. Overall, the CAT GOASSESS showed acceptable psychometric properties and demonstrated feasibility by markedly reducing assessment time compared to the Full GOASSESS. The adaptive version could be used in large-scale studies or clinical settings for intake screening.

Blunted brain responses to neutral faces in healthy first-degree relatives of patients with schizophrenia: an image-based fMRI meta-analysis.

Schizophrenia is characterized by the misattribution of emotional significance to neutral faces, accompanied by overactivations of the limbic system. To understand the disorder's genetic and environmental contributors, investigating healthy first-degree relatives is crucial. However, inconsistent findings exist regarding their ability to recognize neutral faces, with limited research exploring the cerebral correlates of neutral face processing in this population. Thus, we here investigated brain responses to neutral face processing in healthy first-degree relatives through an image-based meta-analysis of functional magnetic resonance imaging studies. We included unthresholded group-level T-maps from 5 studies comprising a total of 120 first-degree relatives and 150 healthy controls. In sensitivity analyses, we ran a combined image- and coordinate-based meta-analysis including 7 studies (157 first-degree relatives, 207 healthy controls) aiming at testing the robustness of the results in a larger sample of studies. Our findings revealed a pattern of decreased brain responses to neutral faces in relatives compared with healthy controls, particularly in limbic areas such as the bilateral amygdala, hippocampus, and insula. The same pattern was observed in sensitivity analyses. These results contrast with the overactivations observed in patients, potentially suggesting that this trait could serve as a protective factor in healthy relatives. However, further research is necessary to test this hypothesis.

Applicability of the CT Radiomics of Skeletal Muscle and Machine Learning for the Detection of Sarcopenia and Prognostic Assessment of Disease Progression in Patients with Gastric and Esophageal Tumors.

PURPOSE: Sarcopenia is considered a negative prognostic factor in patients with malignant tumors. Among other diagnostic options, computed tomography (CT), which is repeatedly performed on tumor patients, can be of further benefit. The present study aims to establish a framework for classifying the impact of sarcopenia on the prognosis of patients diagnosed with esophageal or gastric cancer. Additionally, it explores the significance of CT radiomics in both diagnostic and prognostic methodologies. MATERIALS AND METHODS: CT scans of 83 patients with esophageal or gastric cancer taken at the time of diagnosis and during a follow-up period of one year were evaluated retrospectively. A total of 330 CT scans were analyzed. Seventy three of these patients received operative tumor resection after neoadjuvant chemotherapy, and 74% of the patients were male. The mean age was 64 years (31-83 years). Three time points (t) were defined as a basis for the statistical analysis in order to structure the course of the disease: t1 = initial diagnosis, t2 = following (neoadjuvant) chemotherapy and t3 = end of the first year after surgery in the "surgery" group or end of the first year after chemotherapy. Sarcopenia was determined using the psoas muscle index (PMI). The additional analysis included the analysis of selected radiomic features of the psoas major, quadratus lumborum, and erector spinae muscles at the L3 level. Disease progression was monitored according to the response evaluation criteria in solid tumors (RECIST 1.1). CT scans and radiomics were used to assess the likelihood of tumor progression and their correlation to sarcopenia. For machine learning, the established algorithms decision tree (DT), K-nearest neighbor (KNN), and random forest (RF) were applied. To evaluate the performance of each model, a 10-fold cross-validation as well as a calculation of Accuracy and Area Under the Curve (AUC) was used. RESULTS: During the observation period of the study, there was a significant decrease in PMI. This was most evident in patients with surgical therapy in the comparison between diagnosis and after both neoadjuvant therapy and surgery (each p < 0.001). Tumor progression (PD) was not observed significantly more often in the patients with sarcopenia compared to those without sarcopenia at any time point (p = 0.277 to p = 0.465). On average, PD occurred after 271.69 ± 104.20 days. The time from initial diagnosis to PD in patients "with sarcopenia" was not significantly shorter than in patients "without sarcopenia" at any of the time points (p = 0.521 to p = 0.817). The CT radiomics of skeletal muscle could predict both sarcopenia and tumor progression, with the best results for the psoas major muscle using the RF algorithm. For the detection of sarcopenia, the Accuracy was 0.90 ± 0.03 and AUC was 0.96 ± 0.02. For the prediction of PD, the Accuracy was 0.88 ± 0.04 and the AUC was 0.93 ± 0.04. CONCLUSIONS: In the present study, the CT radiomics of skeletal muscle together with machine learning correlated with the presence of sarcopenia, and this can additionally assist in predicting disease progression. These features can be classified as promising alternatives to conventional methods, with great potential for further research and future clinical application. However, when sarcopenia was diagnosed with PMI, no significant correlation between sarcopenia and PD could be observed.

Voltage-Controlled ON-OFF-Switching of Magnetoresistance in FeOx/Fe/Au Aerogel Networks.

Voltage control of magnetoresistance (MR) in nanoscale three-dimensional (3D) geometries is interesting from a fundamental point of view and a promising route toward novel sensors and energy-efficient computing schemes. Magneto-ionic mechanisms are favorable for low-voltage control of magnetism and room-temperature operation, but magneto-ionic control of MR has been studied only for planar geometries so far. We synthesize a 3D nanomaterial with magneto-ionic functionality by electrodepositing an iron hydroxide/iron coating on a porous nanoscale gold network (aerogel). To enable maximum magneto-ionic ON-OFF-switching, the thickness of the coating is adjusted to a few nanometers by a self-terminating electrodeposition process. In situ magnetotransport measurements during electrolytic gating of these nanostructures reveal large reversible changes in MR, including ON-OFF-switching of MR, with a small applied voltage difference (1.72 V). This effect is related to the electrochemical switching between a ferromagnetic iron shell/gold core nanostructure (negative MR at the reduction voltage) and an iron oxide shell/gold core nanostructure (negligible MR at the oxidation voltage).

Validation of the cognitive section of the Penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT-CCNB).

BACKGROUND: The Penn Computerized Neurocognitive Battery is an efficient tool for assessing brain-behavior domains, and its efficiency was augmented via computerized adaptive testing (CAT). This battery requires validation in a separate sample to establish psychometric properties. METHODS: In a mixed community/clinical sample of N = 307 18-to-35-year-olds, we tested the relationships of the CAT tests with the full-form tests. We compared discriminability among recruitment groups (psychosis, mood, control) and examined how their scores relate to demographics. CAT-Full relationships were evaluated based on a minimum inter-test correlation of 0.70 or an inter-test correlation within at least 0.10 of the full-form correlation with a previous administration of the full battery. Differences in criterion relationships were tested via mixed models. RESULTS: Most tests (15/17) met the minimum criteria for replacing the full-form with the updated CAT version (mean r = 0.67; range = 0.53-0.80) when compared to relationships of the full-forms with previous administrations of the full-forms (mean r = 0.68; range = 0.50-0.85). Most (16/17) CAT-based relationships with diagnostics and other validity criteria were indistinguishable (interaction p > 0.05) from their full-form counterparts. CONCLUSIONS: The updated CNB shows psychometric properties acceptable for research. The full-forms of some tests should be retained due to insufficient time savings to justify the loss in precision.

Evaluation of a nurse-led multi-component transition program for adolescents with congenital heart disease.

OBJECTIVE: To evaluate the effectiveness of the transition program for adolescents with congenital heart disease (CHD) 'Transition With a Heart' (TWAH) on disease-related knowledge, quality of life (QoL), transition experiences, and gaps in follow-up. METHODS: A study with pre-posttest and control group (post-test) using consecutive sampling, including adolescents with moderate to severely complex CHD, without intellectual disability, aged≥ 12 y, and parents. After weighting, t-tests were performed. A multivariable regression analysis explored the outcomes' determinants. RESULTS: In the intervention group, 28 adolescents and 25 parents were included, and 53 adolescents and 18 parents as controls. Adolescents' knowledge significantly increased after completing TWAH (from 59.8% to 75.7%;p < 0.01). Their knowledge was positively correlated with TWAH (ß = +13.3;p < 0.01). Adolescents' transition experiences were also positively related to TWAH (general experience: ß = +5.5;p < 0.01; transfer satisfaction: ß = +0.8; p < 0.01). Adolescents' QoL was mainly determined by CHD complexity and not by TWAH. No one showed gaps in follow-up. TWAH was not associated with parents' transition experiences. CONCLUSION: Implementing TWAH substantially improved adolescents' disease-related knowledge and transition experiences. PRACTICE IMPLICATIONS: The results regarding transition experiences need to be confirmed by further research. The TWAH design with the person-tailored educational program, skills training, and the transition coordinator can be used in settings with other chronic diseases.

Radiomics and Clinicopathological Characteristics for Predicting Lymph Node Metastasis in Testicular Cancer.

Accurate prediction of lymph node metastasis (LNM) in patients with testicular cancer is highly relevant for treatment decision-making and prognostic evaluation. Our study aimed to develop and validate clinical radiomics models for individual preoperative prediction of LNM in patients with testicular cancer. We enrolled 91 patients with clinicopathologically confirmed early-stage testicular cancer, with disease confined to the testes. We included five significant clinical risk factors (age, preoperative serum tumour markers AFP and B-HCG, histotype and BMI) to build the clinical model. After segmenting 273 retroperitoneal lymph nodes, we then combined the clinical risk factors and lymph node radiomics features to establish combined predictive models using Random Forest (RF), Light Gradient Boosting Machine (LGBM), Support Vector Machine Classifier (SVC), and K-Nearest Neighbours (KNN). Model performance was assessed by the area under the receiver operating characteristic (ROC) curve (AUC). Finally, the decision curve analysis (DCA) was used to evaluate the clinical usefulness. The Random Forest combined clinical lymph node radiomics model with the highest AUC of 0.95 (±0.03 SD; 95% CI) was considered the candidate model with decision curve analysis, demonstrating its usefulness for preoperative prediction in the clinical setting. Our study has identified reliable and predictive machine learning techniques for predicting lymph node metastasis in early-stage testicular cancer. Identifying the most effective machine learning approaches for predictive analysis based on radiomics integrating clinical risk factors can expand the applicability of radiomics in precision oncology and cancer treatment.

Genomic loci influence patterns of structural covariance in the human brain.

Normal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to patterns of structural covariance (PSC) across brain regions and individuals during brain aging and diseases. The genetic underpinnings of these patterns remain largely unknown. We apply a stochastic multivariate factorization method to a diverse population of 50,699 individuals (12 studies and 130 sites) and derive data-driven, multi-scale PSCs of regional brain size. PSCs were significantly correlated with 915 genomic loci in the discovery set, 617 of which are newly identified, and 72% were independently replicated. Key pathways influencing PSCs involve reelin signaling, apoptosis, neurogenesis, and appendage development, while pathways of breast cancer indicate potential interplays between brain metastasis and PSCs associated with neurodegeneration and dementia. Using support vector machines, multi-scale PSCs effectively derive imaging signatures of several brain diseases. Our results elucidate genetic and biological underpinnings that influence structural covariance patterns in the human brain.

Self-supervised pre-training with contrastive and masked autoencoder methods for dealing with small datasets in deep learning for medical imaging.

Deep learning in medical imaging has the potential to minimize the risk of diagnostic errors, reduce radiologist workload, and accelerate diagnosis. Training such deep learning models requires large and accurate datasets, with annotations for all training samples. However, in the medical imaging domain, annotated datasets for specific tasks are often small due to the high complexity of annotations, limited access, or the rarity of diseases. To address this challenge, deep learning models can be pre-trained on large image datasets without annotations using methods from the field of self-supervised learning. After pre-training, small annotated datasets are sufficient to fine-tune the models for a specific task. The most popular self-supervised pre-training approaches in medical imaging are based on contrastive learning. However, recent studies in natural image processing indicate a strong potential for masked autoencoder approaches. Our work compares state-of-the-art contrastive learning methods with the recently introduced masked autoencoder approach "SparK" for convolutional neural networks (CNNs) on medical images. Therefore, we pre-train on a large unannotated CT image dataset and fine-tune on several CT classification tasks. Due to the challenge of obtaining sufficient annotated training data in medical imaging, it is of particular interest to evaluate how the self-supervised pre-training methods perform when fine-tuning on small datasets. By experimenting with gradually reducing the training dataset size for fine-tuning, we find that the reduction has different effects depending on the type of pre-training chosen. The SparK pre-training method is more robust to the training dataset size than the contrastive methods. Based on our results, we propose the SparK pre-training for medical imaging tasks with only small annotated datasets.

Dopaminergic Input Regulates the Sensitivity of Indirect Pathway Striatal Spiny Neurons to Brain-Derived Neurotrophic Factor.

Motor dysfunction in Parkinson's disease (PD) is closely linked to the dopaminergic depletion of striatal neurons and altered synaptic plasticity at corticostriatal synapses. Dopamine receptor D1 (DRD1) stimulation is a crucial step in the formation of long-term potentiation (LTP), whereas dopamine receptor D2 (DRD2) stimulation is needed for the formation of long-term depression (LTD) in striatal spiny projection neurons (SPNs). Tropomyosin receptor kinase B (TrkB) and its ligand brain-derived neurotrophic factor (BDNF) are centrally involved in plasticity regulation at the corticostriatal synapses. DRD1 activation enhances TrkB's sensitivity for BDNF in direct pathway spiny projection neurons (dSPNs). In this study, we showed that the activation of DRD2 in cultured striatal indirect pathway spiny projection neurons (iSPNs) and cholinergic interneurons causes the retraction of TrkB from the plasma membrane. This provides an explanation for the opposing synaptic plasticity changes observed upon DRD1 or DRD2 stimulation. In addition, TrkB was found within intracellular structures in dSPNs and iSPNs from Pitx3-/- mice, a genetic model of PD with early onset dopaminergic depletion in the dorsolateral striatum (DLS). This dysregulated BDNF/TrkB signaling might contribute to the pathophysiology of direct and indirect pathway striatal projection neurons in PD.

2D High-Temperature Superconductor Integration in Contact Printed Circuit Boards.

Inherent properties of superconducting Bi2Sr2CaCu2O8+x films, such as the high superconducting transition temperature Tc, efficient Josephson coupling between neighboring CuO layers, and fast quasiparticle relaxation dynamics, make them a promising platform for advances in quantum computing and communication technologies. However, preserving two-dimensional superconductivity during device fabrication is an outstanding experimental challenge because of the fast degradation of the superconducting properties of two-dimensional flakes when they are exposed to moisture, organic solvents, and heat. Herein, to realize superconducting devices utilizing two-dimensional (2D) superconducting films, we develop a novel fabrication technique relying on the cryogenic dry transfer of printable circuits embedded into a silicon nitride membrane. This approach separates the circuit fabrication stage requiring chemically reactive substances and ionizing physical processes from the creation of the thin superconducting structures. Apart from providing electrical contacts in a single transfer step, the membrane encapsulates the surface of the crystal, shielding it from the environment. The fabricated atomically thin Bi2Sr2CaCu2O8+x-based devices show a high superconducting transition temperature of Tc ≃ 91 K close to that of the bulk crystal and demonstrate stable superconducting properties.

Long-term follow-up of atrioventricular valve function in Fontan patients: effect of atrioventricular valve surgery.

OBJECTIVES: The aim of this study was to evaluate the relationship between atrioventricular valve and ventricular function in Fontan survivors, including the effect of atrioventricular valve surgery. METHODS: Analysis focused on transplant-free survival and the need for atrioventricular valve surgery in single ventricle patients after Fontan completion. Longitudinal echocardiographic examination of long-term valve and ventricular function was performed. RESULTS: Fontan completion was performed in 113 patients, having a right univentricular morphology in 33.6%, a left ventricle morphology in 62.8% and ambiguous in 3.6%. Perioperative mortality was 2.7% (n = 3). Within a median follow-up of 16.3 years (interquartile range 10.6-23.6), transplant-free survival was 96.1 ± 1.9% and 90.4 ± 5.8% at 10-25 years. Twenty AV valve procedures were performed in 14 (12.4%) children, respectively, pre-Fontan (n = 10), per-Fontan (n = 8) and post-Fontan (n = 2), resulting in a cumulative incidence of AV valve surgery is 5.7 ± 2.2% and 12.3 ± 3.2% at 1-5 years. Atrio-ventricular valve function deteriorated over time [hazard ratio (HR) 1.112, 95% confidence interval (CI) 1.089-1.138, P < 0.001], without difference for valve morphology (P = 0.736) or ventricular dominance (P = 0.484). AV valve dysfunction was greater in patients requiring AV valve surgery (HR 20.383, 95% CI 6.223-36.762, P < 0.001) but showed a comparable evolution since repair to those without valve surgery (HR 1.070, 95% CI 0.987-1.160, P = 0.099). Progressive time-related ventricular dysfunction was observed (HR 1.141, 95% CI 1.097-1.182, P < 0.001), significantly less in left ventricle-dominance (HR 0.927, 95% CI 0.860-0.999, P = 0.047) but more after AV valve surgery (HR 1.103, 95% CI 1.014-1.167, P = 0.022). CONCLUSIONS: In a homogeneously treated Fontan population, 25-year transplant-free survival is encouraging. Atrio-ventricular valve surgery was necessary in 12.4%, resulting mostly in a durable valve function. However, a slow time-related decline of atrioventricular valve function as of ventricular function is worrisome, evoking a role for additional heart failure therapy.

Evaluation of a new intrinsic and extrinsic motivation scale in youth with psychosis spectrum symptoms.

BACKGROUND: Impairment in intrinsic motivation (IM), the drive to satisfy internal desires like mastery, may play a key role in disability in psychosis. However, we have limited knowledge regarding relative impairments in IM compared to extrinsic motivation (EM) or general motivation (GM), in part due to limitations in existing measures. METHODS: Here we address this gap using a novel Trait Intrinsic and Extrinsic Motivation self-report scale in a sample of n = 243 participants including those with schizophrenia, psychosis-risk, and healthy controls. Each of the 7 IM and 6 EM items used a 7-point Likert scale assessing endorsement of dispositional statements. Bifactor analyses of these items yielded distinct IM, EM, and GM factor scores. Convergent and discriminant validity were examined in relation to General Causality Orientation Scale (GCOS-CP) and Quality of Life 3-item IM measure (QLS-IM). Utility was assessed in relation to psychosis-spectrum (PS) status and CAINS clinical amotivation. RESULTS: IM and EM showed acceptable inter-item consistency (IM: α = 0.88; EM: α = 0.66); the bifactor model exhibited fit that varied from good to borderline to inadequate depending on the specific fit metric (SRMR = 0.038, CFI = 0.94, RMSEA = 0.106 ± 0.014). IM scores correlated with established IM measures: GCOS-CP Autonomy (rho = 0.38, p < 0.01) and QLS-IM (rho = 0.29, p < 0.01). Supporting discriminant validity, IM did not correlate with GCOS-CP Control (rho = -0.14, p > 0.05). Two-year stability in an available longitudinal subset (n = 35) was strong (IM: rho = 0.64, p < 0.01; EM: rho = 0.55, p < 0.01). Trait IM was lower in PS youth (t = 4.24, p < 0.01), and correlated with clinical amotivation (rho = -0.36, p < 0.01); EM did not show significant clinical associations. CONCLUSIONS: These results demonstrate the clinical relevance of IM in psychosis risk. They also provide preliminary support for the reliability, validity and utility of this new Trait IM-EM scale, which addresses a measurement gap and can facilitate identification of neurobehavioral and clinical correlates of IM deficits.

Evaluation of late cardiac effects after multisystem inflammatory syndrome in children.

Introduction: Multisystem inflammatory syndrome in children (MIS-C) is associated with important cardiovascular morbidity during the acute phase. Follow-up shows a swift recovery of cardiac abnormalities in most patients. However, a small portion of patients has persistent cardiac sequelae at mid-term. The goal of our study was to assess late cardiac outcomes of MIS-C. Methods: A prospective observational multicenter study was performed in children admitted with MIS-C and cardiac involvement between April 2020 and March 2022. A follow-up by NT-proBNP measurement, echocardiography, 24-h Holter monitoring, and cardiac MRI (CMR) was performed at least 6 months after MIS-C diagnosis. Results: We included 36 children with a median age of 10 (8.0-11.0) years, and among them, 21 (58%) were girls. At diagnosis, all patients had an elevated NT-proBNP, and 39% had a decreased left ventricular ejection fraction (LVEF) (<55%). ECG abnormalities were present in 13 (36%) patients, but none presented with arrhythmia. Almost two-thirds of patients (58%) had echocardiographic abnormalities such as coronary artery dilation (20%), pericardial effusion (17%), and mitral valve insufficiency (14%). A decreased echocardiographic systolic left ventricular (LV) function was detected in 14 (39%) patients. A follow-up visit was done at a mean time of 12.1 (±5.8) months (range 6-28 months). The ECG normalized in all except one, and no arrhythmias were detected on 24-h Holter monitoring. None had persistent coronary artery dilation or pericardial effusion. The NT-proBNP level and echocardiographic systolic LV function normalized in all patients, except for one, who had a severely reduced EF. The LV global longitudinal strain (GLS), as a marker of subclinical myocardial dysfunction, decreased (z < -2) in 35%. CMR identified one patient with severely reduced EF and extensive myocardial fibrosis requiring heart transplantation. None of the other patients had signs of myocardial scarring on CMR. Conclusion: Late cardiac outcomes after MIS-C, if treated according to the current guidelines, are excellent. CMR does not show any myocardial scarring in children with normal systolic LV function. However, a subgroup had a decreased GLS at follow-up, possibly as a reflection of persistent subclinical myocardial dysfunction.

WRAP: A wavelet-regularised reconstruction algorithm for magnetic vector electron tomography.

Magnetic vector electron tomography (VET) is a promising technique that enables better understanding of micro- and nano-magnetic phenomena through the reconstruction of 3D magnetic fields at high spatial resolution. Here we introduce WRAP (Wavelet Regularised A Program), a reconstruction algorithm for magnetic VET that directly reconstructs the magnetic vector potential A using a compressed sensing framework which regularises for sparsity in the wavelet domain. We demonstrate that using WRAP leads to a significant increase in the fidelity of the 3D reconstruction and is especially robust when dealing with very limited data; using datasets simulated with realistic noise, we compare WRAP to a conventional reconstruction algorithm and find an improvement of ca. 60% when averaged over several performance metrics. Moreover, we further validate WRAP's performance on experimental electron holography data, revealing the detailed magnetism of vortex states in a CuCo nanowire. We believe WRAP represents a major step forward in the development of magnetic VET as a tool for probing magnetism at the nanoscale.