Search results
Found 8058 matches for
ZFP36-family RNA-binding proteins in regulatory T cells reinforce immune homeostasis
RNA binding proteins (RBP) of the ZFP36 family limit the differentiation and effector functions of CD4 and CD8 T cells, but little is known of their expression or function in regulatory T (Treg) cells. By using Treg cell-restricted deletion of Zfp36 family members we identify the role of Zfp36l1 and Zfp36l2 in Treg cells to maintain immune homeostasis. Mice with Treg cells deficient in these RBP display an inflammatory phenotype with an expansion in the numbers of type-2 conventional dendritic cells, T effector cells, T follicular helper and germinal center B cells and elevated serum cytokines and immunoglobulins. In the absence of Zfp36l1 and Zfp36l2, the pool of cycling CTLA-4 in naïve Treg cells is reduced, Treg cells are less sensitive to IL-2 and IL-7 but are more sensitive to IFNγ. In mice lacking both RBP in Treg cells, the deletion of a single allele of Ifng is sufficient to ameliorate the pathology. Our results indicate that ZFP36L1 and ZFP36L2 regulate the availability of IFNγ and are required for the maintenance of Treg cell stability. Thus, ZFP36L1 and ZFP36L2 regulate multiple pathways that enable Treg cells to enforce immune homeostasis.
Low-Rank Conjugate Gradient-Net for Accelerated Cardiac MR Imaging
Cardiovascular diseases (CVDs) remain the leading cause of mortality and morbidity worldwide. Both diagnosis and prognosis of these diseases benefit from high-quality imaging, which cardiac magnetic resonance imaging provides. CMR imaging requires lengthy acquisition times and multiple breath-holds for a complete exam, which can lead to patient discomfort and frequently results in image artifacts. In this work, we present a Low-rank tensor U-Net method (LowRank-CGNet) that rapidly reconstructs highly undersampled data with a variety of anatomy, contrast, and undersampling artifacts. The model uses conjugate gradient data consistency to solve for the spatial and temporal bases and employs a U-Net to further regularize the basis vectors. Currently, model performance is superior to a standard U-Net, but inferior to conventional compressed sensing methods. In the future, we aim to further improve model performance by increasing the U-Net size, extending the training duration, and dynamically updating the tensor rank for different anatomies.
Smartphone-based Monitoring and cognition Modification Against Recurrence of Depression (SMARD): An RCT of Memory Bias Modification Training vs. Cognitive Control Training vs. Attention Bias Modification Training in remitted recurrently depressed patients with 1.5 year follow-up.
BACKGROUND: Major Depressive Disorder (MDD) has a 50-80% recurrence rate highlighting the urgent need for more efficient recurrence prevention programs. Currently, recurrences are often identified too late, while existing preventive strategies may not sufficiently address ethio-patho-physiological mechanisms for recurrence. Negative memory bias (the tendency to better remember negative than positive events), negative attention bias (selective attention favoring mood-congruent information), and cognitive control deficits are important factors involved in the onset, maintenance, and recurrence of depressive episodes. METHODS: Here we describe the protocol for the Smartphone-based Monitoring and cognition Modification Against Recurrence of Depression (SMARD) study, aiming to investigate different forms of cognitive training programs administered via smartphones, in order to develop a second-generation recurrence prevention program. In addition, we will gather Experience Sampling Method (ESM) assessments during a 6-day period, and during the follow-up period we will obtain behavioral data on (social) activities with BEHAPP, a smartphone-based Mobile Passive Monitoring application for remote behavioral monitoring to identify behavioral changes indicative of an imminent depressive episode. In a randomized controlled trial, SMARD will compare the effects of a smartphone-based Memory Bias Modification Training (MBT), Cognitive Control Training (CCT), and Attention Bias Modification Training (ABT) versus cognitive domain-specific (active-) sham trainings in 120 remitted MDD-patients with recurrent-MDD. Over the course of three weeks, participants receive multiple daily training sessions. Thereafter, participants will be followed up for 1.5 years with 3-monthly interviews to assess recurrences. DISCUSSION: The SMARD study aims to 1. assess the effects of the cognitive training programs versus their training-specific (active-) sham conditions on changes in memory, cognitive control dysfunction and attention; 2. relate training effects to neural networks previously identified in (recurrence of) MDD (therefore we obtain functional Magnetic Resonance Imaging ((f)MRI) scans before and after the training in a subset of participants); 3. link baseline and change in memory, cognitive control, attention and neural functioning, and ESM data to prospective recurrences; 4. examine whether passive smartphone-use monitoring can be used for prediction of recurrences. TRIAL REGISTRATION: NL-OMON26184 and NL-OMON27513. Registered 12 August 2021-Retrospectively registered, https://onderzoekmetmensen.nl/en/trial/26184 en https://onderzoekmetmensen.nl/en/trial/27513 .
Cholinergic degeneration in prodromal and early Parkinson's: a link to present and future disease states.
The neuropathological process in Parkinson's disease (PD) and Lewy body disorders has been shown to extend well beyond the degeneration of the dopaminergic system, affecting other neuromodulatory systems in the brain which play crucial roles in the clinical expression and progression of these disorders. Here, we investigate the role of the macrostructural integrity of the nucleus basalis of Meynert (NbM), the main source of cholinergic input to the cerebral cortex, in cognitive function, clinical manifestation, and disease progression in non-demented subjects with PD and individuals with isolated REM sleep behaviour disorder (iRBD). Using structural MRI data from 393 early PD patients, 128 iRBD patients, and 186 controls from two longitudinal cohorts, we found significantly lower NbM grey matter volume in both PD (β=-12.56, p=0.003) and iRBD (β=-16.41, p=0.004) compared to controls. In PD, higher NbM volume was associated with better higher-order cognitive function (β=0.10, p=0.045), decreased non-motor (β=-0.66, p=0.026) and motor (β=-1.44, p=0.023) symptom burden, and lower risk of future conversion to dementia (Hazard ratio (HR)<0.400, p<0.004). Higher NbM volume in iRBD was associated with decreased future risk of phenoconversion to PD or dementia with Lewy bodies (DLB) (HR<0.490, p<0.016). However, despite similar NbM volume deficits to those seen in PD, associations between NbM structural deficits and current disease burden or clinical state were less pronounced in iRBD. These findings identify NbM volume as a potential biomarker with dual utility: predicting cognitive decline and disease progression in early PD, while also serving as an early indicator of phenoconversion risk in prodromal disease. The presence of structural deficits before clear clinical correlates in iRBD suggests complex compensatory mechanisms may initially mask cholinergic dysfunction, with subsequent failure of these mechanisms potentially contributing to clinical conversion.
The Effects of Facilitation and Inhibition During Multimodal Somatosensory Integration
The somatosensory system, including modalities such as touch, temperature, and pain, is essential for perceiving and interacting with the environment. When individuals encounter different somatosensory modalities, they interact through a process called multimodal somatosensory integration. This integration is essential for accurate perception, motor coordination, pain management, and adaptive behavior. Disruptions in this process can lead to a variety of sensory disorders and complicate rehabilitation efforts. However, research on the behavioral patterns and neural mechanisms underlying multimodal somatosensory integration remains limited. According to previous studies, multimodal somatosensory integration can result in facilitative or inhibitory effects depending on factors like stimulus type, intensity, and spatial proximity. Facilitative effects are observed primarily when stimuli from the same sensory modality (e. g., two touch or temperature stimuli) are presented simultaneously, leading to amplified perceptual strength and quicker reaction times. Additionally, certain external factors, such as cooling, can increase sensitivity to other sensory inputs, further promoting facilitative integration. In contrast, inhibitory effects may also emerge when stimuli from different sensory modalities interact, particularly between touch and pain. Under such conditions, one sensory input (e.g., vibration or non-noxious temperature stimulation) can effectively reduce the perceived intensity of the other, often resulting in reduced pain perception. These facilitative and inhibitory interactions are critical for efficient processing in a multi-stimulus environment and play a role in modulating the experience of somatosensory inputs in both normal and clinical contexts. The neural mechanisms underlying multimodal somatosensory integration are multi-tiered, encompassing peripheral receptors, the spinal cord, and various cortical structures. Facilitative integration relies on the synchronous activation of peripheral receptors, which transmit enhanced signals to higher processing centers. At the cortical level, areas such as the primary and secondary somatosensory cortex, through multimodal neuron responses, facilitate combined representation and amplification of sensory signals. In particular, the thalamus is a significant relay station where multisensory neurons exhibit superadditive responses, contributing to facilitation by enhancing signal strength when multiple inputs are present. Inhibitory integration, on the other hand, is mediated by mechanisms within the spinal cord, such as gating processes that limit transmission of competing sensory signals, thus diminishing the perceived intensity of certain inputs. At the cortical level, lateral inhibition within the somatosensory cortex plays a key role in reducing competing signals from non-target stimuli, enabling prioritized processing of the most relevant sensory input. This layered neural architecture supports the dynamic modulation of sensory inputs, balancing facilitation and inhibition to optimize perception. Understanding the neural pathways involved in somatosensory integration has potential clinical implications for diagnosing sensory disorders and developing therapeutic strategies. Future research should focus on elucidating the specific neural circuitry and mechanisms that contribute to these complex interactions, providing insights into the broader implications of somatosensory integration on behavior and cognition. In summary, this review highlights the importance of multimodal somatosensory integration in enhancing sensory perception. It also underscores the need for further exploration into the neural underpinnings of these processes to advance our understanding of sensory integration and its applications in clinical settings.
Exploration of brain-spinal cord-gut axis abnormalities and the mechanism of acupuncture therapy in irritable bowel syndrome based on magnetic resonance imaging
Irritable bowel syndrome (IBS) is a functional gastrointestinal disorder triggered by the disorder of brain-gut interaction and characterized by abdominal pain, bloating, and altered bowel habits. It is estimated to affect between 5% and 10% of the global population. Although IBS does not have an excessive mortality rate, the disease significantly affects the quality of life and can lead to significant disability. Current treatments mainly focus on relieving abdominal pain and improving bowel habits. However, the effect of drug therapy on the overall symptoms of patients is limited, and the majority of therapeutic drugs are associated with the risk of adverse reactions. Consequently, many patients turn to complementary and alternative therapies to achieve more favorable treatment outcomes. Acupuncture, as a complementary and alternative therapy, has shown potential in the treatment of IBS. Although clinical trials have confirmed the therapeutic effect of acupuncture, its mechanism of action remains unclear, leading to controversy in the global medical community. Researchers, leveraging magnetic resonance imaging (MRI) technology, strive to delve deeply into the biological mechanisms underlying the alleviation of irritable bowel syndrome symptoms through acupuncture therapy, aiming to provide solid support for the scientific basis and efficacy of this treatment method. However, current imaging research primarily focuses on changes in brain structure and function, relatively neglecting the close connection between spinal structure and function and IBS. The spinal cord plays a crucial role in brain-gut interaction, and the development of MRI technology provides a new perspective for exploring the pathogenesis of IBS and the mechanism of acupuncture based on the brain-spinal cord-gut axis. This paper reviews MRI-based studies on abnormalities in brain-spinal cord-gut axis interaction in IBS and acupuncture treatment. Although there have been significant advancements in understanding the causes and using acupuncture to treat IBS, there are still several limitations that need to be addressed. One limitation is the insufficient number of imaging studies on the spinal cord, which hinders our comprehensive understanding of the development of IBS and the underlying mechanisms of acupuncture therapy. In the future, it is necessary to enhance the imaging study of the spinal cord and conduct a thorough analysis of the brain-spinal cord-gut axis mechanism. This will enable us to establish a scientific foundation for understanding the pathogenesis of IBS and the effectiveness of acupuncture treatment. Furthermore, the current research on the impact of acupuncture on IBS primarily concentrates on describing the phenomenon and comparing data but fails to incorporate the principles of neuroscience pain theory. In the future, it is important to prioritize the integration of pain theory and thoroughly investigate the impact of acupuncture on the primary pathways of pain transmission and processing. This will help us understand the intricate mechanism of acupuncture analgesia and facilitate the broader application of acupuncture therapy.
AnchorInv: Few-Shot Class-Incremental Learning of Physiological Signals via Feature Space-Guided Inversion
Deep learning models have demonstrated exceptional performance in a variety of real-world applications. These successes are often attributed to strong base models that can generalize to novel tasks with limited supporting data while keeping prior knowledge intact. However, these impressive results are based on the availability of a large amount of high-quality data, which is often lacking in specialized biomedical applications. In such fields, models are usually developed with limited data that arrive incrementally with novel categories. This requires the model to adapt to new information while preserving existing knowledge. Few-Shot Class-Incremental Learning (FSCIL) methods offer a promising approach to addressing these challenges, but they also depend on strong base models that face the same aforementioned limitations. To overcome these constraints, we propose AnchorInv following the straightforward and efficient buffer-replay strategy. Instead of selecting and storing raw data, AnchorInv generates synthetic samples guided by anchor points in the feature space. This approach protects privacy and regularizes the model for adaptation. When evaluated on three public physiological time series datasets, AnchorInv exhibits efficient knowledge forgetting prevention and improved adaptation to novel classes, surpassing state-of-the-art baselines.
Automated quality control of T1-weighted brain MRI scans for clinical research datasets: methods comparison and design of a quality prediction classifier
Abstract T1-weighted (T1w) MRI is widely used in clinical neuroimaging for studying brain structure and its changes, including those related to neurodegenerative diseases, and as anatomical reference for analysing other modalities. Ensuring high-quality T1w scans is vital as image quality affects reliability of outcome measures. However, visual inspection can be subjective and time-consuming, especially with large datasets. The effectiveness of automated quality control (QC) tools for clinical cohorts remains uncertain. In this study, we used T1w scans from elderly participants within ageing and clinical populations to test the accuracy of existing QC tools with respect to visual QC and to establish a new quality prediction framework for clinical research use. Four datasets acquired from multiple scanners and sites were used (N = 2438, 11 sites, 39 scanner manufacturer models, 3 field strengths – 1.5T, 3T, 2.9T, patients and controls, average age 71 ± 8 years). All structural T1w scans were processed with two standard automated QC pipelines (MRIQC and CAT12). The agreement of the accept-reject ratings was compared between the automated pipelines and with visual QC. We then designed a quality prediction framework that combines the QC measures from the existing automated tools and is trained on clinical research datasets. We tested the classifier performance using cross-validation on data from all sites together, also examining the performance across diagnostic groups. We then tested the generalisability of our approach when leaving one site out and explored how well our approach generalises to data from a different scanner manufacturer and/or field strength from those used for training, as well as on an unseen new dataset of healthy young participants with movement related artefacts. Our results show significant agreement between automated QC tools and visual QC (Kappa=0.30 with MRIQC predictions; Kappa=0.28 with CAT12’s rating) when considering the entire dataset, but the agreement was highly variable across datasets. Our proposed robust undersampling boost (RUS) classifier achieved 87.7% balanced accuracy on the test data combined from different sites (with 86.6% and 88.3% balanced accuracy on scans from patients and controls respectively). This classifier was also found to be generalisable on different combinations of training and test datasets (average balanced accuracy of leave-one-site-out = 78.2%; exploratory models on field strengths and manufacturers = 77.7%; movement related artefact dataset when including 1% scans in the training = 88.5%). While existing QC tools may not be robustly applicable to datasets comprised of older adults, they produce quality metrics that can be leveraged to train a more robust quality control classifiers for ageing and clinical cohorts.
Working memory filtering at encoding and maintenance in healthy ageing, Alzheimer's and Parkinson's disease.
The differential impact on working memory (WM) performance of distractors presented at encoding or during maintenance was investigated in Alzheimer's Disease (AD), Parkinson's Disease (PD) patients, elderly (EHC) and young healthy controls (YHC), (n = 28 per group). Participants reported the orientation of an arrow from a set of either two or three items, with a distractor present either at encoding or at maintenance. MRI data with hippocampal volumes was also acquired. Mean absolute error and mixture model metrics i.e., memory precision, target detection, misbinding (swapping the features of an object with another probed item) and guessing were computed. EHC and PD patients showed good filtering abilities both at encoding and maintenance. However, AD patients exhibited significant filtering deficits specifically when the distractor appeared during maintenance. In healthy ageing there was a prominent decline in WM memory precision, whilst in AD lower target detection and higher guessing were the main sources of error. Conversely, PD was associated only with higher guessing rates. Hippocampal volume was significantly correlated with filtering during maintenance - but not at encoding. These findings demonstrate how healthy ageing and neurodegenerative diseases exhibit distinct patterns of WM impairment, including when filtering irrelevant material either at encoding and maintenance.
Dorsomedial and ventromedial prefrontal cortex lesions differentially impact social influence and temporal discounting.
The medial prefrontal cortex (mPFC) has long been associated with economic and social decision-making in neuroimaging studies. Several debates question whether different ventral mPFC (vmPFC) and dorsal mPFC (dmPFC) regions have specific functions or whether there is a gradient supporting social and nonsocial cognition. Here, we tested an unusually large sample of rare participants with focal damage to the mPFC (N = 33), individuals with lesions elsewhere (N = 17), and healthy controls (N = 71) (total N = 121). Participants completed a temporal discounting task to estimate their baseline discounting preferences before learning the preferences of two other people, one who was more temporally impulsive and one more patient. We used Bayesian computational models to estimate baseline discounting and susceptibility to social influence after learning others' economic preferences. mPFC damage increased susceptibility to impulsive social influence compared to healthy controls and increased overall susceptibility to social influence compared to those with lesions elsewhere. Importantly, voxel-based lesion-symptom mapping (VLSM) of computational parameters showed that this heightened susceptibility to social influence was attributed specifically to damage to the dmPFC (area 9; permutation-based threshold-free cluster enhancement (TFCE) p < 0.025). In contrast, lesions in the vmPFC (areas 13 and 25) and ventral striatum were associated with a preference for seeking more immediate rewards (permutation-based TFCE p < 0.05). We show that the dmPFC is causally implicated in susceptibility to social influence, with distinct ventral portions of mPFC involved in temporal discounting. These findings provide causal evidence for sub-regions of the mPFC underpinning fundamental social and cognitive processes.
In Vivo Quantification of Creatine Kinase Kinetics in Mouse Brain Using 31P-MRS at 7 T
31P-MRS is a method of choice for studying neuroenergetics in vivo, but its application in the mouse brain has been limited, often restricted to ultrahigh field (> 7 T) MRI scanners. Establishing its feasibility on more readily available preclinical 7-T scanners would create new opportunities to study metabolism and physiology in murine models of brain disorders. Here, we demonstrate that the apparent forward rate constant (kf) of creatine kinase (CK) can be accurately quantified using a progressive saturation-transfer approach in the mouse brain at 7 T. We also find that a 20% reduction in respiration of anesthetized mice can lead to 36% increase in kf attributable to a drop in cellular pH and mitochondrial ATP production. To achieve this, we used a test–retest analysis to assess the reliability and repeatability of 31P-MRS acquisition, analysis, and experimental design protocols. We report that many 31P-containing metabolites can be reliably measured using a localized 3D-ISIS sequence, which showed highest SNR amplitude, SNR consistency, and minimal T2 relaxation signal loss. Our study identifies key physiological factors influencing mouse brain energy homeostasis in vivo and provides a methodological basis to guide future studies interested in implementing 31P-MRS on preclinical 7-T scanners.
A single dose of lamotrigine induces a positive memory bias in healthy volunteers.
BACKGROUND: Lamotrigine has been shown to be effective in the long-term treatment and relapse prevention of depression in bipolar disorder. However, the neuropsychological mechanisms underlying these effects are unclear. We investigated the effects of lamotrigine on a battery of emotional processing tasks in healthy volunteers, previously shown to be sensitive to antidepressant drug action in similar experimental designs. METHODS: Healthy volunteers (n = 36) were randomized in a double-blind design to receive a single dose of placebo or 300 mg lamotrigine. Mood and subjective effects were monitored throughout the study period, and emotional processing was assessed using the Oxford Emotional Test Battery (ETB) 3 hours post-administration. RESULTS: Participants receiving lamotrigine showed increased accurate recall of positive versus negative self-descriptors, compared to those in the placebo group. There were no other significant effects on emotional processing in the ETB, and lamotrigine did not affect ratings of mood or subjective experience. CONCLUSIONS: Lamotrigine did not induce widespread changes in emotional processing. However, there was increased positive bias in emotional memory, similar to the effects of antidepressants reported in previous studies. Further work is needed to assess whether similar effects are seen in the clinical treatment of patients with bipolar disorder and the extent to which this is associated with its clinical action in relapse prevention.
Future directions for brain health clinics.
Brain Health Services are second-generation memory clinics that aim to reduce the risk of progression to dementia in at-risk individuals. We describe the rationale for such a service, and comment on its novel implementation by Venkataraman and colleagues that integrates digital technologies and biomarker testing. We describe the advantages and possible limitations of such an approach, then investigate areas for further work - namely, the need to account for multiple pathologies in biomarker testing and to formulate standards for genetic counselling.
Dopamine D2 receptor upregulation in dorsal striatum in the LRRK2-R1441C rat model of early Parkinson's disease revealed by in vivo PET imaging.
We conducted PET imaging with [18F]FDOPA and dopamine D2/3 receptor ligand [18F]fallypride in aged transgenic rats carrying human pathogenic LRRK2 R1441C or G2019S mutations. These rats have mild age-dependent deficits in dopamine release restricted to dorsal striatum despite no overt loss of dopamine neurons or dopamine content and demonstrate L-DOPA-responsive movement deficits.LRRK2 mutant rats displayed no deficit in [18F]FDOPA uptake, consistent with intact dopamine synthesis in striatal axons. However, LRRK2-R1441C rats demonstrated greater binding of [18F]fallypride than LRRK2-G2019S or non-transgenic controls, from a regionally selective increase in dorsal striatum. Immunocytochemical labelling post-mortem confirmed a greater density of D2 receptors in LRRK2-R1441C than other genotypes restricted to dorsal striatum, consistent with upregulation of D2-receptors as a compensatory response to the greater dopamine release deficit previously demonstrated in this genotype.These results show that [18F]fallypride PET imaging is sensitive to dysregulation of dopamine signalling in the LRRK2-R1441C rat, revealing upregulation of D2 receptors that parallels observations in human putamen in early sporadic PD. Future studies of candidate therapies could exploit this non-invasive approach to assess treatment efficacy.