PET imaging of GABA receptors in pancreatic islets by [C]flumazenil.

Background: Type 1 diabetes (T1D) is an autoimmune disease characterized by a progressive β-cell destruction. There are no clinically established methods for quantifying endocrine cells of the pancreas and current knowledge is almost exclusively based on autopsy material and functional measurements. Based on the expression of the γ-aminobutyric acid A receptors (GABARs) in pancreatic islets and the fact that GABAR agonists are being explored as treatment for T1D, we hypothesized that the positron emission tomography (PET) tracer [C]flumazenil ([C]FMZ) could serve as a marker of the endocrine mass of the pancreas.

Sensing equivalent kinematics enables robot-assisted mirror rehabilitation training via a broaden learning system.

Introduction: Robot-assisted mirror therapy has been widely developed to help remodeling of premotor cortex for patients suffering from motor disability of limbs. Nevertheless, it is difficult to achieve real-time adaptive control in robot-assisted mirror rehabilitation training, particularly for patients with varying levels of limb impairment.

Methods: This paper proposes an equivalent kinematics control framework based on the Broaden Learning System model for active robotic mirror rehabilitation, where people's bilateral upper limbs actively perform mirror movements to enhance the impaired limb's participation.

Prognostic Value of Pre-Operative Transthoracic Echocardiography in Patients with Primary Mitral Regurgitation.

Mitral regurgitation is the second most prevalent valvular disease, with primary mitral regurgitation (PMR) accounting for 61%-67% of cases. Chronic PMR can result in progressive left ventricular remodeling and dysfunction, ultimately leading to heart failure or other adverse cardiac events. This, in turn, necessitates frequent referrals, hospitalizations, and cardiac surgeries.

Left Ventricular 3-Dimensional Global Longitudinal Strain Predicts All-Cause Mortality in Patients With Heart Transplant.

Background: The prognostic value of 3-dimensional (3D)-left ventricular global longitudinal strain (LVGLS) in recipients of heart transplant (HT) reremains unknown. This study aimed to determine whether 3D-LVGLS was the more powerful predictor of poor outcomes in recipients of HT compared with 2-dimensional (2D)-LVGLS.

Methods And Results: All consecutive adult patients who received HT and underwent at least 1 comprehensive 2D and 3D transthoracic echocardiographic examination for clinical surveillance were retrospectively enrolled.

Unraveling the Diffusion MRI-Based Glymphatic System Alterations in Children with Rolandic Epilepsy.

Rationale And Objectives: Although dysfunction of the glymphatic system in adult epilepsy has been extensively studied, there is a lack of research on the changes in this system during childhood development, particularly in children with Rolandic epilepsy (RE). This study aimed to investigate the changes in diffusion MRI measures related to the glymphatic function in children with RE.

Materials And Methods: A total of thirty-eight children with RE and thirty-six demographically matched healthy children were enrolled in the study.

Brain structural connectomic topology predicts medication response in youth with bipolar disorder: A randomized clinical trial.

Background: Response to pharmacotherapy varies considerably among youths with bipolar disorder (BD) and is poorly predicted by clinical or demographic features. It can take several weeks to determine whether medication for BD is clinically effective. Although neuroimaging biomarkers are promising predictors, few studies examined the predictive value of the brain connectomic topology.

The emerging field of non-invasive brain stimulation in Alzheimer's disease.

Treating cognitive impairment is a holy grail of modern clinical neuroscience. In the past few years, non-invasive brain stimulation is increasingly emerging as a therapeutic approach to ameliorate performance in patients with cognitive impairment and as an augmentation approach in persons whose cognitive performance is within normal limits. In patients with Alzheimer's disease, better understanding of brain connectivity and function has allowed for the development of different non-invasive brain stimulation protocols.

Altered Neural Processing of Interoception in Patients With Functional Neurological Disorder: A Task-Based fMRI Study.

Objective: Research suggests that disrupted interoception contributes to the development and maintenance of functional neurological disorder (FND); however, no functional neuroimaging studies have examined the processing of interoceptive signals in patients with FND.

Methods: The authors examined univariate and multivariate functional MRI neural responses of 38 patients with mixed FND and 38 healthy control individuals (HCs) during a task exploring goal-directed attention to cardiac interoception-versus-control (exteroception or rest) conditions. The relationships between interoception-related neural responses, heartbeat-counting accuracy, and interoceptive trait prediction error (ITPE) were also investigated for FND patients.

MRI-based radiomics machine learning model to differentiate non-clear cell renal cell carcinoma from benign renal tumors.

Purpose: We aim to develop an MRI-based radiomics model to improve the accuracy of differentiating non-ccRCC from benign renal tumors preoperatively.

Methods: The retrospective study included 195 patients with pathologically confirmed renal tumors (134 non-ccRCCs and 61 benign renal tumors) who underwent preoperative renal mass protocol MRI examinations. The patients were divided into a training set (n = 136) and test set (n = 59).

Diagnostic accuracy and image quality evaluation of ultrashort echo time MRI in the lungs.

This study evaluates the diagnostic accuracy of ultrashort echo time (UTE)-MRI for detecting pulmonary nodules and image quality. A total of 46 patients at our hospital underwent unenhanced computed tomography (CT) and UTE-MRI. The image quality and number of nodules detected using CT were used as the gold standards.

The application of artificial intelligence in diabetic retinopathy: progress and prospects.

In recent years, artificial intelligence (AI), especially deep learning models, has increasingly been integrated into diagnosing and treating diabetic retinopathy (DR). From delving into the singular realm of ocular fundus photography to the gradual development of proteomics and other molecular approaches, from machine learning (ML) to deep learning (DL), the journey has seen a transition from a binary diagnosis of "presence or absence" to the capability of discerning the progression and severity of DR based on images from various stages of the disease course. Since the FDA approval of IDx-DR in 2018, a plethora of AI models has mushroomed, gradually gaining recognition through a myriad of clinical trials and validations.

Out-of-distribution detection in digital pathology: Do foundation models bring the end to reconstruction-based approaches?

Artificial intelligence (AI) has shown promising results for computational pathology tasks. However, one of the limitations in clinical practice is that these algorithms are optimised for the distribution represented by the training data. For out-of-distribution (OOD) data, they often deliver predictions with equal confidence, even though these often are incorrect.

Aberrant dynamic functional network connectivity in patients with diffuse axonal injury.

Diffuse axonal injury (DAI) results in aberrant functional connectivity and is significantly linked to cognitive impairment. Nevertheless, the network mechanisms influencing neurocognitive function following DAI remain unclear. This study aimed to examine the characteristics of static and dynamic functional network connectivity (FNC) in patients with DAI.

FNDC4 alleviates cardiac ischemia/reperfusion injury through facilitating HIF1α-dependent cardiomyocyte survival and angiogenesis in male mice.

Fibronectin type III domain-containing (FNDC) proteins play critical roles in cellular homeostasis and cardiac injury, and our recent findings define FNDC5 as a promising cardioprotectant against doxorubicin- and aging-related cardiac injury. FNDC4 displays a high homology with FNDC5; however, its role and mechanism in cardiac ischemia/reperfusion (I/R) injury remain elusive. Here, we show that cardiac and plasma FNDC4 levels are elevated during I/R injury in a hypoxia-inducible factor 1α (HIF1α)-dependent manner.

Effects of List-Mode-Based Intraframe Motion Correction in Dynamic Brain PET Imaging.

Motion is unavoidable in dynamic [F]-MK6240 Positron Emission Tomography (PET) imaging, especially in Alzheimer's disease (AD) research requiring long scan duration. To understand how motion correction affects quantitative analysis, we investigated two approaches: II-MC, which corrects for both inter-frame and intra-frame motion, and IO-MC, which only corrects for inter-frame motion. These methods were applied to 83 scans from 34 subjects, and we calculated distribution volume ratios (DVR) using the multilinear reference tissue model with two parameters (MRTM2) in tau-rich brain regions.

Synthesis and mechanistic investigation of BPA fluorescent probes targeting BPA for potential application in Boron Neutron Capture Therapy (BNCT).

Boronic acid analogs are crucial in modern organic chemistry and drug development, serving as versatile reagents and intermediates with significant therapeutic applications. This area has gained increased interest with the recent development of the drug 4-boron-L-phenylalanine (L-BPA) for boron neutron capture therapy (BNCT). Fluorescent probe technology offers an essential pathway for imaging drugs in vitro and in vivo, providing high sensitivity with great spatial and temporal resolution for both disease diagnosis and drug development.

Anodal tDCS improves neuromuscular adaptations to short-term resistance training of the knee extensors in healthy individuals.

Experimental studies show improvement in physical performance following acute application of transcranial direct current stimulation (tDCS). This study examined the neuromuscular and neural responses to a single training session () and following a 3 wk resistance training program () performed with the knee extensors, preceded by tDCS over the primary motor cortex. Twenty-four participants (age, 30 ± 7 yr; stature, 172 ± 8 cm; mass, 72 ± 15 kg) were randomly allocated to perform either resistance training with anodal tDCS (a-tDCS) or a placebo tDCS (Sham).

Treatment-wise Glioblastoma Survival Inference with Multi-parametric Preoperative MRI.

In this work, we aim to predict the survival time (ST) of glioblastoma (GBM) patients undergoing different treatments based on preoperative magnetic resonance (MR) scans. The personalized and precise treatment planning can be achieved by comparing the ST of different treatments. It is well established that both the current status of the patient (as represented by the MR scans) and the choice of treatment are the cause of ST.