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.

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.

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.

Predicting Outcome in Clear Aligner Treatment: A Machine Learning Analysis.

Background/Objectives: Machine learning (ML) models predicting the risk of refinement (i.e., a subsequent course of treatment being necessary) in clear aligner therapy (CAT) were developed and evaluated. Methods: An anonymized sample of 9942 CAT patients (70.6% females, 29.4% males, age range 18-64 years, median 30.5 years), as provided by DrSmile, a large European CAT provider based in Berlin, Germany, was used. Three different ML methods were employed: (1) logistic regression with L1 regularization, (2) extreme gradient boosting (XGBoost), and (3) support vector classification with a radial basis function kernel. In total, 74 factors were selected as predictors for these methods and are consistent with clinical reasoning. Results: On a held-out test set with a true-positive rate of 0.58, the logistic regression model has an area under the ROC curve (AUC) of 0.67, an average precision (AP) of 0.73, and Brier loss of 0.22; the XGBoost model has an AUC of 0.67, an AP of 0.74, and Brier loss of 0.22; and the support vector model has a recall of 0.61 and a precision of 0.64. The logistic regression and XGBoost models identify predictors influencing refinement risk, including patient compliance, interproximal enamel reduction (IPR) and certain planned tooth movements, for example, lingual translation of maxillary incisors being associated with the lowest risk of refinement and rotation of mandibular incisors with the highest risk. Conclusions: These findings suggest moderate, well-calibrated predictive accuracy with both regularized logistic regression and XGBoost and underscore the influence the identified factors have on the risk of refinement in CAT, emphasizing their importance in the careful planning of orthodontic treatment and the potential for shorter treatment times, less patient discomfort, and fewer clinic visits. Identification of at-risk individuals could support tailored clinical decision-making and enable targeted interventions.

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.

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).

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.

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.

Social effort discounting reveals domain-general and social-specific motivation components.

BACKGROUND: Social motivation is crucial for healthy interpersonal connections and is impaired in a subset of the general population and across many psychiatric disorders. However, compared to nonsocial (e.g., monetary) motivation, social motivation has been understudied in quantitative behavioral work, especially regarding willingness to exert social effort. We developed a novel social effort discounting task, paired with a monetary task to examine motivational specificity. We expected social task performance would relate to general motivation also show selective relationships with self-reported avoidance tendencies and with sociality. METHODS: An analyzed sample of 397 participants performed the social and nonsocial effort discounting task online, along with self-report measures of various aspects of motivation and psychiatric symptomatology. RESULTS: Social and nonsocial task motivation correlated strongly (rho=0.71 p<0.001). Both social and nonsocial task motivation related similarly to self-reported general motivation (social ß=0.16; nonsocial ß=0.13) and to self-reported approach motivation (social ß=0.14; nonsocial ß=0.11), with this common effect captured by a significant main effect across social and nonsocial conditions. Significant condition interaction effects supported a selective relationship of social task motivation with self-reported sociality and also with avoidance motivation. CONCLUSIONS: Our novel social effort discounting task revealed both domain-general and social-specific components of motivation. In combination with other measures, this approach can facilitate further investigation of common and dissociable neurobehavioral mechanisms, in order to better characterize normative and pathological variation and develop personalized interventions targeting specific contributors to social impairment.

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.

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.

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.

Interfacial Distortion of Sb2Te3-Sb2Se3 Multilayers via Atomic Layer Deposition for Enhanced Thermoelectric Properties.

Atomic layer deposition (ALD) is an effective technique for depositing thin films with precise control of layer thickness and functional properties. In this work, Sb2Te3-Sb2Se3 nanostructures were synthesized using thermal ALD. A decrease in the Sb2Te3 layer thickness led to the emergence of distinct peaks from the Laue rings, indicative of a highly textured film structure with optimized crystallinity. Density functional theory simulations revealed that carrier redistribution occurs at the interface to establish charge equilibrium. By carefully optimizing the layer thicknesses, we achieved an obvious enhancement in the Seebeck coefficient, reaching a peak figure of merit (zT) value of 0.38 at room temperature. These investigations not only provide strong evidence for the potential of ALD manipulation to improve the electrical performance of metal chalcogenides but also offer valuable insights into achieving high performance in two-dimensional materials.

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.

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.

Multimodality 3D image fusion with live fluoroscopy reduces radiation dose during catheterization of congenital heart defects.

Introduction: Imaging fusion technology is promising as it is radiation and contrast sparing. Herein, we compare conventional biplane angiography to multimodality image fusion with live fluoroscopy using two-dimensional (2D)-three-dimensional (3D) registration (MMIF2D-3D) and assess MMIF2D-3D impact on radiation exposure and contrast volume during cardiac catheterization of patients with congenital heart disease (CHD). Methods: We matched institutional MMIF2D-3D procedures and controls according to patient characteristics (body mass index, age, and gender) and the seven procedure-type subgroups. Then, we matched the number of tests and controls per subgroup using chronological ordering or propensity score matching. Subsequently, we combined the matched subgroups into larger subgroups of similar procedure type, keeping subgroups with at least 10 test and 10 control cases. Air kerma (AK) and dose area product (DAP) were normalized by body weight (BW), product of body weight and fluoroscopy time (BW × FT), or product of body weight and number of frames (BW × FR), and stratified by acquisition plane and irradiation event type (fluoroscopy or acquisition). Three senior interventionists evaluated the relevance of MMIF2D-3D (5-point Likert scale). Results: The Overall group consisted of 54 MMIF2D-3D cases. The combined and matched subgroups were pulmonary artery stenting (StentPUL), aorta angioplasty (PlastyAO), pulmonary artery angioplasty (PlastyPUL), or a combination of the latter two (Plasty). The FT of the lateral plane reduced significantly by 69.6% for the Overall MMIF2D-3D population. AKBW and DAPBW decreased, respectively, by 43.9% and 39.3% (Overall group), 49.3% and 54.9% (PlastyAO), and 36.7% and 44.4% for the Plasty subgroup. All the aforementioned reductions were statistically significant except for DAPBW in the Overall and Plasty (sub)groups. The decrease of AKBW and DAPBW in the StentPUL and PlastyPUL subgroups was not statistically significant. The decrease in the median values of the weight-normalized contrast volume (CMCBW) in all five subgroups was not significant. Cardiologists considered MMIF2D-3D very useful with a median score of 4. Conclusion: In our institution, MMIF2D-3D overall enabled significant AKBW reduction during the catheterization of CHD patients and was mainly driven by reduced FT in the lateral plane. We observed significant AKBW reduction in the Plasty and PlastyAO subgroups and DAPBW reduction in the PlastyAO subgroup. However, the decrease in CMCBW was not significant.