Mitochondrial complex II in intestinal epithelial cells regulates T cell-mediated immunopathology.

Intestinal epithelial cell (IEC) damage by T cells contributes to graft-versus-host disease, inflammatory bowel disease and immune checkpoint blockade-mediated colitis. But little is known about the target cell-intrinsic features that affect disease severity. Here we identified disruption of oxidative phosphorylation and an increase in succinate levels in the IECs from several distinct in vivo models of T cell-mediated colitis. Metabolic flux studies, complemented by imaging and protein analyses, identified disruption of IEC-intrinsic succinate dehydrogenase A (SDHA), a component of mitochondrial complex II, in causing these metabolic alterations. The relevance of IEC-intrinsic SDHA in mediating disease severity was confirmed by complementary chemical and genetic experimental approaches and validated in human clinical samples. These data identify a critical role for the alteration of the IEC-specific mitochondrial complex II component SDHA in the regulation of the severity of T cell-mediated intestinal diseases.

Uridine-derived ribose fuels glucose-restricted pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDA) is a lethal disease notoriously resistant to therapy1,2. This is mediated in part by a complex tumour microenvironment3, low vascularity4, and metabolic aberrations5,6. Although altered metabolism drives tumour progression, the spectrum of metabolites used as nutrients by PDA remains largely unknown. Here we identified uridine as a fuel for PDA in glucose-deprived conditions by assessing how more than 175 metabolites impacted metabolic activity in 21 pancreatic cell lines under nutrient restriction. Uridine utilization strongly correlated with the expression of uridine phosphorylase 1 (UPP1), which we demonstrate liberates uridine-derived ribose to fuel central carbon metabolism and thereby support redox balance, survival and proliferation in glucose-restricted PDA cells. In PDA, UPP1 is regulated by KRAS-MAPK signalling and is augmented by nutrient restriction. Consistently, tumours expressed high UPP1 compared with non-tumoural tissues, and UPP1 expression correlated with poor survival in cohorts of patients with PDA. Uridine is available in the tumour microenvironment, and we demonstrated that uridine-derived ribose is actively catabolized in tumours. Finally, UPP1 deletion restricted the ability of PDA cells to use uridine and blunted tumour growth in immunocompetent mouse models. Our data identify uridine utilization as an important compensatory metabolic process in nutrient-deprived PDA cells, suggesting a novel metabolic axis for PDA therapy.

Maternal and offspring pools of osteocalcin influence brain development and functions.

The powerful regulation of bone mass exerted by the brain suggests the existence of bone-derived signals modulating this regulation or other functions of the brain. We show here that the osteoblast-derived hormone osteocalcin crosses the blood-brain barrier, binds to neurons of the brainstem, midbrain, and hippocampus, enhances the synthesis of monoamine neurotransmitters, inhibits GABA synthesis, prevents anxiety and depression, and favors learning and memory independently of its metabolic functions. In addition to these postnatal functions, maternal osteocalcin crosses the placenta during pregnancy and prevents neuronal apoptosis before embryos synthesize this hormone. As a result, the severity of the neuroanatomical defects and learning and memory deficits of Osteocalcin(-/-) mice is determined by the maternal genotype, and delivering osteocalcin to pregnant Osteocalcin(-/-) mothers rescues these abnormalities in their Osteocalcin(-/-) progeny. This study reveals that the skeleton via osteocalcin influences cognition and contributes to the maternal influence on fetal brain development.

Harmonic field extension for QSM with reduced spatial coverage using physics-informed generative adversarial network.

Quantitative susceptibility mapping (QSM) is frequently employed in investigating brain iron related to brain development and diseases within deep gray matter (DGM). Nonetheless, the acquisition of whole-brain QSM data is time-intensive. An alternative approach, focusing the QSM specifically on areas of interest such as the DGM by reducing the field-of-view (FOV), can significantly decrease scan times. However, severe susceptibility value underestimations have been reported during QSM reconstruction with a limited FOV, largely attributable to artifacts from incorrect background field removal in the boundary region. This presents a considerable barrier to the clinical use of QSM with small spatial coverages using conventional methods alone. To mitigate the propagation of these errors, we proposed a harmonic field extension method based on a physics-informed generative adversarial network. Both quantitative and qualitative results demonstrate that our method outperforms conventional methods and delivers results comparable to those obtained with full FOV. Furthermore, we demonstrate the versatility of our method by applying it to data acquired prospectively with limited FOV and to data from patients with Parkinson's disease. The method has shown significant improvements in local field results, with QSM outcomes. In a clear illustration of its feasibility and effectiveness in real clinical environments, our proposed method addresses the prevalent issue of susceptibility underestimation in QSM with small spatial coverage.

Alterations in the multilayer network in patients with rapid eye movement sleep behaviour disorder.

This study aimed to reveal the pathophysiology of isolated rapid eye movement sleep behaviour disorder (RBD) in patients using multilayer network analysis. Participants eligible for isolated RBD were included and verified via polysomnography. Both iRBD patients and healthy controls underwent brain MRI, including T1-weighted imaging and diffusion tensor imaging. Grey matter matrix was derived from T1-weighted images using a morphometric similarity network. White matter matrix was formed from diffusion tensor imaging-based structural connectivity. Multilayer network analysis of grey and white matter was performed using graph theory. We studied 29 isolated RBD patients and 30 healthy controls. Patients exhibited a higher average overlap degree (27.921 vs. 23.734, p = 0.002) and average multilayer clustering coefficient (0.474 vs. 0.413, p = 0.002) compared with controls. Additionally, several regions showed significant differences in the degree of overlap and multilayer clustering coefficient between patients with isolated RBD and healthy controls at the nodal level. The degree of overlap in the left medial orbitofrontal, left posterior cingulate, and right paracentral nodes and the multilayer clustering coefficients in the left lateral occipital, left rostral middle frontal, right fusiform, right inferior posterior parietal, and right parahippocampal nodes were higher in patients with isolated RBD than in healthy controls. We found alterations in the multilayer network at the global and nodal levels in patients with isolated RBD, and these changes may be associated with the pathophysiology of isolated RBD. Multilayer network analysis can be used widely to explore the mechanisms underlying various neurological disorders.

Three-dimensional heavily T2-weighted FLAIR in the detection of blood-labyrinthine barrier leakage in patients with sudden sensorineural hearing loss: comparison with T1 sequences and application of deep learning-based reconstruction.

OBJECTIVE: Blood-labyrinthine barrier leakage has been reported in sudden sensorineural hearing loss (SSNHL). We compared immediate post-contrast 3D heavily T2-weighted fluid-attenuated inversion recovery (FLAIR), T1 spin echo (SE), and 3D T1 gradient echo (GRE) sequences, and heavily T2-weighted FLAIR (hvT2F) with and without deep learning-based reconstruction (DLR) in detecting perilymphatic enhancement. METHODS: Fifty-four patients with unilateral SSNHL who underwent ear MRI with three sequences were included. We compared asymmetry scores, confidence scores, and detection rates of perilymphatic enhancement among the three sequences and obtained 3D hvT2F with DLR from 35 patients. The above parameters and subjective image quality between 3D hvT2F with and without DLR were compared. RESULTS: Asymmetry scores and detection rate of 3D hvT2F were significantly higher than 3D GRE T1 and SE T1 (respectively, 1.37, 0.11, 0.19; p < 0.001). Asymmetry scores significantly increased with DLR compared to 3D hvT2F for experienced and inexperienced readers (respectively, 1.77 vs. 1.40, p = 0.036; 1.49 vs. 1.03, p = 0.012). The detection rate significantly increased only for the latter (57.1% vs. 31.4%, p = 0.022). Patients with perilymphatic enhancement had significantly higher air conduction thresholds on initial (77.96 vs. 57.79, p = 0.002) and 5 days after presentation (63.38 vs. 41.85, p = 0.019). CONCLUSION: 3D hvT2F significantly increased the detectability of perilymphatic enhancement compared to 3D GRE T1 and SE T1. DLR further improved the conspicuity of perilymphatic enhancement in 3D hvT2F. 3D hvT2F and DLR are useful for evaluating blood-labyrinthine barrier leakage; furthermore, they might provide prognostic value in the early post-treatment period. CLINICAL RELEVANCE STATEMENT: Ten-minute post-contrast 3D heavily T2-weighed FLAIR imaging is a potentially efficacious sequence in demonstrating perilymphatic enhancement in patients with sudden sensorineural hearing loss and may be further improved by deep learning-based reconstruction. KEY POINTS: • 3D heavily T2-weighted FLAIR (3D hvT2F) is a sequence sensitive in detecting low concentrations of contrast in the perilymphatic space. • 3D hvT2F sequences properly demonstrated perilymphatic enhancement in sudden sensorineural hearing loss compared to T1 sequences and were further improved by deep learning-based reconstruction (DLR). • 3D hvT2F and DLR are efficacious sequences in detecting blood-labyrinthine barrier leakage and with potential prognostic information.

Anti-seizure medication response and the glymphatic system in patients with focal epilepsy.

BACKGROUND AND PURPOSE: We aimed to evaluate (i) glymphatic system function in patients with focal epilepsy in comparison with healthy controls, and (ii) the association between anti-seizure medication (ASM) response and glymphatic system function by using diffusion tensor image analysis along the perivascular space (DTI-ALPS). METHODS: We retrospectively enrolled 100 patients with focal epilepsy who had normal brain magnetic resonance imaging (MRI) findings, and classified them as "poor" or "good" ASM responders according to their seizure control at the time of brain MRI. We also included 79 age- and sex-matched healthy controls. All patients and healthy controls underwent conventional brain MRI and diffusion tensor imaging. The DTI-ALPS index was calculated using the DSI studio program. RESULTS: Of the 100 patients with focal epilepsy, 38 and 62 were poor and good ASM responders, respectively. The DTI-ALPS index differed significantly between patients with focal epilepsy and healthy controls and was significantly lower in patients with focal epilepsy (1.55 vs. 1.70; p < 0.001). The DTI-ALPS index also differed significantly according to ASM response and was lower in poor ASM responders (1.48 vs. 1.59; p = 0.047). Furthermore, the DTI-ALPS index was negatively correlated with age (r = -0.234, p = 0.019) and duration of epilepsy (r = -0.240, p = 0.016) in patients with focal epilepsy. CONCLUSION: Our study is the first to identify, in focal epilepsy patients, a greater reduction in glymphatic system function among poor ASM responders compared to good responders. To confirm our results, further prospective multicenter studies with large sample sizes are needed.

Structural connectivity as a predictive factor for responsiveness to levetiracetam treatment in epilepsy.

PURPOSE: To investigate whether structural connectivity or glymphatic system function is a potential predictive factor for levetiracetam (LEV) response in patients with newly diagnosed epilepsy. METHODS: We enrolled patients with newly diagnosed epilepsy who were administered LEV as initial monotherapy and underwent diffusion tensor imaging (DTI) at diagnosis. We categorized the patients into drug response. We used graph theory to calculate the network measures for structural connectivity based on the DTI scans in patients with epilepsy. Additionally, we evaluated glymphatic system function by calculating the DTI analysis along the perivascular space (DTI-ALPS) index based on DTI scans. RESULTS: We enrolled 84 patients with epilepsy. The clinical factors and DTI-ALPS index did not differ between the groups. However, some of the structural connectivity measures significantly differ between the groups. The poor responders exhibited a higher mean clustering coefficient, global efficiency, and small-worldness index than the good responders (p = 0.003, p = 0.048, and p = 0.038, respectively). In the receiver operating characteristic curve analysis, the mean clustering coefficient exhibited the highest performance in predicting the responsiveness to LEV (area under the curve of 0.677). In the multiple logistic regression analysis, the mean clustering coefficient of the structural connectivity measures was the only significant predictor of LEV response (p = 0.014). Furthermore, in the survival analysis, the mean clustering coefficient was the only significant predictor of LEV response (p = 0.026). CONCLUSION: We demonstrated that structural connectivity is a potential predictive factor for responsiveness to LEV treatment in patients with newly diagnosed epilepsy.

Multilayer network analysis in patients with juvenile myoclonic epilepsy.

INTRODUCTION: We conducted a multilayer network analysis in patients with juvenile myoclonic epilepsy (JME) and healthy controls, to investigate the gray matter layer using a morphometric similarity network and analyze the white matter layer using structural connectivity. METHODS: We enrolled 42 patients with newly diagnosed JME and 53 healthy controls. Brain magnetic resonance imaging (MRI) using a three-tesla MRI scanner, including T1-weighted imaging and diffusion tensor imaging (DTI) were performed. We created a gray matter layer matrix with a morphometric similarity network using T1-weighted imaging, and a white matter layer matrix with structural connectivity using the DTI. Subsequently, we performed a multilayer network analysis by applying graph theory. RESULTS: There were significant differences in network at the global level in the multilayer network analysis between the groups. The average multiplex participation of patients with JME was lower than that of healthy controls (0.858 vs. 0.878, p = 0.007). In addition, several regions showed significant differences in multiplex participation at the nodal level in the multilayer network analysis. Multiplex participation in the right entorhinal cortex was lower, whereas multiplex participation in the right supramarginal gyrus was higher at the nodal level in the multilayer network analysis of patients with JME compared to healthy controls. CONCLUSION: We demonstrated differences in network at the global and nodal levels in the multilayer network analysis between patients with JME and healthy controls. These features may be associated with the pathophysiology of JME and could help us understand the complex brain network in patients with JME.

Alteration of multilayer network perspective on gray and white matter connectivity in obstructive sleep apnea.

PURPOSE: The objective of this research was to examine changes in the neural networks of both gray and white matter in individuals with obstructive sleep apnea (OSA) in comparison to those without the condition, employing a comprehensive multilayer network analysis. METHODS: Patients meeting the criteria for OSA were recruited through polysomnography, while a control group of healthy individuals matched for age and sex was also assembled. Utilizing T1-weighted imaging, a morphometric similarity network was crafted to represent gray matter, while diffusion tensor imaging provided structural connectivity for constructing a white matter network. A multilayer network analysis was then performed, employing graph theory methodologies. RESULTS: We included 40 individuals diagnosed with OSA and 40 healthy participants in our study. Analysis revealed significant differences in various global network metrics between the two groups. Specifically, patients with OSA exhibited higher average degree overlap and average multilayer clustering coefficient (28.081 vs. 23.407, p < 0.001; 0.459 vs. 0.412, p = 0.004), but lower multilayer modularity (0.150 vs. 0.175, p = 0.001) compared to healthy controls. However, no significant differences were observed in average multiplex participation, average overlapping strength, or average weighted multiplex participation between the patients with OSA and healthy controls. Moreover, several brain regions displayed notable differences in degree overlap at the nodal level between patients with OSA and healthy controls. CONCLUSION: Remarkable alterations in the multilayer network, indicating shifts in both gray and white matter, were detected in patients with OSA in contrast to their healthy counterparts. Further examination at the nodal level unveiled notable changes in regions associated with cognition, underscoring the effectiveness of multilayer network analysis in exploring interactions across brain layers.

Cerebellar volumes and the intrinsic cerebellar network in patients with obstructive sleep apnea.

PURPOSE: This research aimed to explore changes in both cerebellar volume and the intrinsic cerebellar network in patients with obstructive sleep apnea (OSA). METHODS: Newly diagnosed OSA patients and healthy controls were included in the study. All participants underwent three-dimensional T1-weighted imaging using a 3-T MRI scanner. Cerebellar volumes, both overall and subdivided, were quantified using the ACAPULCO program. The intrinsic cerebellar network was assessed using the BRAPH program, which applied graph theory to the cerebellar volume subdivision. Comparisons were drawn between the patients with OSA and healthy controls. RESULTS: The study revealed that the 26 patients with OSA exhibited a notably lower total cerebellar volume compared to the 28 healthy controls (8.330 vs. 9.068%, p < 0.001). The volume of the left lobule VIIB was reduced in patients with OSA compared to healthy controls (0.339 vs. 0.407%, p = 0.001). Among patients with OSA, there was a negative correlation between the volume of the left lobule X and apnea-hypopnea index during non-rapid eye movement sleep (r = - 0.536, p = 0.005). However, no significant differences were observed in the intrinsic cerebellar network between patients and healthy controls. CONCLUSION: This study established that patients with OSA exhibited decreased total cerebellar volumes and particularly reduced volumes in subdivisions such as the left lobule VIIB compared to healthy controls. These findings suggest potential involvement of the cerebellum in the underlying mechanisms of OSA.

KmerKeys: a web resource for searching indexed genome assemblies and variants.

K-mers are short DNA sequences that are used for genome sequence analysis. Applications that use k-mers include genome assembly and alignment. However, the wider bioinformatic use of these short sequences has challenges related to the massive scale of genomic sequence data. A single human genome assembly has billions of k-mers. As a result, the computational requirements for analyzing k-mer information is enormous, particularly when involving complete genome assemblies. To address these issues, we developed a new indexing data structure based on a hash table tuned for the lookup of short sequence keys. This web application, referred to as KmerKeys, provides performant, rapid query speeds for cloud computation on genome assemblies. We enable fuzzy as well as exact sequence searches of assemblies. To enable robust and speedy performance, the website implements cache-friendly hash tables, memory mapping and massive parallel processing. Our method employs a scalable and efficient data structure that can be used to jointly index and search a large collection of human genome assembly information. One can include variant databases and their associated metadata such as the gnomAD population variant catalogue. This feature enables the incorporation of future genomic information into sequencing analysis. KmerKeys is freely accessible at https://kmerkeys.dgi-stanford.org.

Analysis of Failure Mechanism and Reliability Enhancement of Silicon Strain Gauge-Based Pressure Sensor for Automotive Applications.

Hydrogen fuel cell vehicles have gained more attention as future automobiles due to their environmental benefits and extended driving ranges. Concurrently, the global hydrogen sensor market is also experiencing substantial growth. These sensors are integrated into vehicles to detect hydrogen leakage and concentration, thereby ensuring the safety of hydrogen fuel cell vehicles. In particular, hydrogen pressure sensors, commonly installed on the manifold and regulator of vehicles, can measure hydrogen pressure and diagnose safety concerns caused by hydrogen leakage in advance. In this paper, we identify the vulnerable points of hydrogen pressure sensors when exposed to vehicle driving environments, investigate failure mechanisms, and provide process optimization techniques. Specifically, our reliability modeling verifies that the components of a printed circuit board (PCB) exposed to humid environments undergo corrosion due to ion migration, leading to the generation of extrinsic series or parallel resistances, which in turn cause fluctuations of output voltage. Through structural and elemental analysis, we pinpoint process-related factors that make components vulnerable to humidity, thereby suggesting recommendations for enhancing the manufacturing process. Based on this analysis in the development stage, we can proactively address and improve reliability and further safety-related issues for future automobiles, thus preventing real field issues.

Single-cell analysis can define distinct evolution of tumor sites in follicular lymphoma.

Tumor heterogeneity complicates biomarker development and fosters drug resistance in solid malignancies. In lymphoma, our knowledge of site-to-site heterogeneity and its clinical implications is still limited. Here, we profiled 2 nodal, synchronously acquired tumor samples from 10 patients with follicular lymphoma (FL) using single-cell RNA, B-cell receptor (BCR) and T-cell receptor sequencing, and flow cytometry. By following the rapidly mutating tumor immunoglobulin genes, we discovered that BCR subclones were shared between the 2 tumor sites in some patients, but in many patients, the disease had evolved separately with limited tumor cell migration between the sites. Patients exhibiting divergent BCR evolution also exhibited divergent tumor gene-expression and cell-surface protein profiles. While the overall composition of the tumor microenvironment did not differ significantly between sites, we did detect a specific correlation between site-to-site tumor heterogeneity and T follicular helper (Tfh) cell abundance. We further observed enrichment of particular ligand-receptor pairs between tumor and Tfh cells, including CD40 and CD40LG, and a significant correlation between tumor CD40 expression and Tfh proliferation. Our study may explain discordant responses to systemic therapies, underscores the difficulty of capturing a patient's disease with a single biopsy, and furthers our understanding of tumor-immune networks in FL.

In vitro modeling of liver fibrosis with 3D co-culture system using a novel human hepatic stellate cell line.

Hepatic stellate cells (HSCs) play an important role in liver fibrosis; however, owing to the heterogeneity and limited supply of primary HSCs, the development of in vitro liver fibrosis models has been impeded. In this study, we established and characterized a novel human HSC line (LSC-1), and applied it to various types of three-dimensional (3D) co-culture systems with differentiated HepaRG cells. Furthermore, we compared LSC-1 with a commercially available HSC line on conventional monolayer culture. LSC-1 exhibited an overall upregulation of the expression of fibrogenic genes along with increased levels of matrix and adhesion proteins, suggesting a myofibroblast-like or transdifferentiated state. However, activated states reverted to a quiescent-like phenotype when cultured in different 3D culture formats with a relatively soft microenvironment. Additionally, LSC-1 exerted an overall positive effect on co-cultured differentiated HepaRG, which significantly increased hepatic functionality upon long-term cultivation compared with that achieved with other HSC line. In 3D spheroid culture, LSC-1 exhibited enhanced responsiveness to transforming growth factor beta 1 exposure that is caused by a different matrix-related protein expression mechanism. Therefore, the LSC-1 line developed in this study provides a reliable candidate model that can be used to address unmet needs, such as development of antifibrotic therapies.

Structural brain network analysis in occipital lobe epilepsy.

BACKGROUND: This study aimed to analyze the structural brain network in patients with occipital lobe epilepsy (OLE) and investigate the differences in structural brain networks between patients with OLE and healthy controls. METHODS: Patients with OLE and healthy controls with normal brain MRI findings were enrolled. They underwent diffusion tensor imaging using a 3.0T MRI scanner, and we computed the network measures of global and local structural networks in patients with OLE and healthy controls using the DSI studio program. We compared network measures between the groups. RESULTS: We enrolled 23 patients with OLE and 42 healthy controls. There were significant differences in the global structural network between patients with OLE and healthy controls. The assortativity coefficient (-0.0864 vs. -0.0814, p = 0.0214), mean clustering coefficient (0.0061 vs. 0.0064, p = 0.0203), global efficiency (0.0315 vs. 0.0353, p = 0.0086), and small-worldness index (0.0001 vs. 0.0001, p = 0.0175) were lower, whereas the characteristic path length (59.2724 vs. 53.4684, p = 0.0120) was higher in patients with OLE than those in the healthy controls. There were several nodes beyond the occipital lobe that showed significant differences in the local structural network between the groups. In addition, the assortativity coefficient was negatively correlated with the duration of epilepsy (r=-0.676, p = 0.001).

Cardiovascular Event Rates in Statin-Treated Korean Patients with Cardiovascular Disease: Estimates from a Real-World Population Using Electronic Medical Record Data.

PURPOSE: To estimate the risk of recurrent cardiovascular events in a real-world population of very high-risk Korean patients with prior myocardial infarction (MI), ischemic stroke (IS), or symptomatic peripheral artery disease (sPAD), similar to the Further cardiovascular OUtcomes Research with proprotein convertase subtilisin-kexin type 9 Inhibition in subjects with Elevated Risk (FOURIER) trial population. METHODS: This retrospective study used the Asan Medical Center Heart Registry database built on electronic medical records (EMR) from 2000 to 2016. Patients with a history of clinically evident atherosclerotic cardiovascular disease (ASCVD) with multiple risk factors were followed up for 3 years. The primary endpoint was a composite of MI, stroke, hospitalization for unstable angina, coronary revascularization, and all-cause mortality. RESULTS: Among 15,820 patients, the 3-year cumulative incidence of the composite primary endpoint was 15.3% and the 3-year incidence rate was 5.7 (95% CI 5.5-5.9) per 100 person-years. At individual endpoints, the rates of deaths, MI, and IS were 0.4 (0.3-0.4), 0.9 (0.8-0.9), and 0.8 (0.7-0.9), respectively. The risk of the primary endpoint did not differ significantly between recipients of different intensities of statin therapy. Low-density lipoprotein cholesterol (LDL-C) goals were only achieved in 24.4% of patients during the first year of follow-up. CONCLUSION: By analyzing EMR data representing routine practice in Korea, we found that patients with very high-risk ASCVD were at substantial risk of further cardiovascular events in 3 years. Given the observed risk of recurrent events with suboptimal lipid management by statin, additional treatment to control LDL-C might be necessary to reduce the burden of further cardiovascular events for very high-risk ASCVD patients.

Involvement of the default mode network in patients with transient global amnesia: multilayer network.

INTRODUCTION: We aimed to investigate the alterations in the multilayer network in patients with transient global amnesia (TGA). METHODS: We enrolled 124 patients with TGA and 80 healthy controls. Both patients with TGA and healthy controls underwent a three-teslar brain magnetic resonance imaging (MRI). A gray matter layer matrix was created using a morphometric similarity network derived from the T1-weighted imaging, and a white matter layer matrix was constructed using structural connectivity based on the diffusion tensor imaging. A multilayer network analysis was performed by applying graph theoretical analysis. RESULTS: There were no significant differences in global network measures between the groups. However, several regions, related to the default mode network, showed significant differences in nodal network measures between the groups. Multi-richness in the left pars opercularis, multi-rich-club degree in the right posterior cingulate gyrus, and weighted multiplex participation in the right posterior cingulate gyrus were higher in patients with TGA compared with healthy controls (15.47 vs. 12.26, p = 0.0005; 41.68 vs. 37.16, p = 0.0005; 0.90 vs. 0.80, p = 0.0005; respectively). The multiplex core-periphery in the left precuneus was higher (0.96 vs. 0.84, p = 0.0005), whereas that in the transverse temporal gyrus was lower in patients with TGA compared with healthy controls (0.00 vs. 0.02, p = 0.0005). CONCLUSION: We newly find the alterations in the multilayer network in patients with TGA compared with healthy controls, which shows the involvement of the default mode network. These changes may be related to the pathophysiology of TGA.

Rewiring the taste system.

In mammals, taste buds typically contain 50-100 tightly packed taste-receptor cells (TRCs), representing all five basic qualities: sweet, sour, bitter, salty and umami. Notably, mature taste cells have life spans of only 5-20 days and, consequently, are constantly replenished by differentiation of taste stem cells. Given the importance of establishing and maintaining appropriate connectivity between TRCs and their partner ganglion neurons (that is, ensuring that a labelled line from sweet TRCs connects to sweet neurons, bitter TRCs to bitter neurons, sour to sour, and so on), we examined how new connections are specified to retain fidelity of signal transmission. Here we show that bitter and sweet TRCs provide instructive signals to bitter and sweet target neurons via different guidance molecules (SEMA3A and SEMA7A). We demonstrate that targeted expression of SEMA3A or SEMA7A in different classes of TRCs produces peripheral taste systems with miswired sweet or bitter cells. Indeed, we engineered mice with bitter neurons that now responded to sweet tastants, sweet neurons that responded to bitter or sweet neurons responding to sour stimuli. Together, these results uncover the basic logic of the wiring of the taste system at the periphery, and illustrate how a labelled-line sensory circuit preserves signalling integrity despite rapid and stochastic turnover of receptor cells.

Cerebellar Volume Reduction in Patients with Isolated REM Sleep Behavior Disorder: Evidence of a Potential Role of the Cerebellum.

INTRODUCTION: In this study, we aimed to investigate changes in the total cerebellar volume, subdivisions of the cerebellar volume, and intrinsic cerebellar network in patients with isolated rapid eye movement (REM) sleep behavior disorder (iRBD) compared to healthy controls. METHODS: We enrolled patients with newly diagnosed iRBD and healthy controls who had no structural lesions according to their brain MRI. All participants underwent three-dimensional T1-weighted imaging. We obtained the total cerebellar volume and subdivisions of the cerebellar volume using the ACAPULCO program and calculated the intrinsic cerebellar network using a BRAPH program based on the subdivisions of the cerebellar volume by applying a graph theory. We compared the cerebellar volumes and intrinsic cerebellar network between the patients with iRBD and healthy controls. RESULTS: In total, we enrolled 43 patients with iRBD and 47 healthy controls. Total cerebellar volume in patients with iRBD was lower than that in the healthy controls (8.4637 vs. 9.0863%, p = 0.0001). There were significant differences in the subdivisions of cerebellar volume between the groups. The volumes of the right and left lobule VIIB in the patients with iRBD were lower than those in the healthy controls (right, 0.3495 vs. 0.4025%, p = 0.0009; left, 0.3561 vs. 0.4293%, p < 0.0001). However, the other cerebellar volumes, such as the corpus meullare and vermis, were not different between the groups. The intrinsic cerebellar network was not different between the patients with iRBD and healthy controls. CONCLUSION: We found decreased total cerebellar volumes and subdivisions of the cerebellar volume, particularly in the right and left lobule VIIB, in patients with iRBD compared to healthy controls. The present results suggest that the cerebellum may play a potential role in the pathogenesis of iRBD.