Machine-learning classifier models for predicting sarcopenia in the elderly based on physical factors.

AIM: As the size of the elderly population gradually increases, musculoskeletal disorders, such as sarcopenia, are increasing. Diagnostic techniques such as X-rays, computed tomography, and magnetic resonance imaging are used to predict and diagnose sarcopenia, and methods using machine learning are gradually increasing. This study aimed to create a model that can predict sarcopenia using physical characteristics and activity-related variables without medical diagnostic equipment, such as imaging equipment, for the elderly aged 60 years or older. METHODS: A sarcopenia prediction model was constructed using public data obtained from the Korea National Health and Nutrition Examination Survey. Models were built using Logistic Regression, Support Vector Machine (SVM), XGBoost, LightGBM, RandomForest, and Multi-layer Perceptron Neural Network (MLP) algorithms, and the feature importance of the models trained with the algorithms, except for SVM and MLP, was analyzed. RESULTS: The sarcopenia prediction model built with the LightGBM algorithm achieved the highest test accuracy, of 0.848. In constructing the LightGBM model, physical characteristic variables such as body mass index, weight, and waist circumference showed high importance, and activity-related variables were also used in constructing the model. CONCLUSIONS: The sarcopenia prediction model, which consisted of only physical characteristics and activity-related factors, showed excellent performance. This model has the potential to assist in the early detection of sarcopenia in the elderly, especially in communities with limited access to medical resources or facilities. Geriatr Gerontol Int 2024; ••: ••-••.

CSF pulsations measured in Parkinson's disease patients using EPI-based fMRI data.

Introduction: Cerebrospinal fluid (CSF) flow is involved in brain waste clearance and may be impaired in neurodegenerative diseases such as Parkinson's disease. This study aims to investigate the relationship between the CSF pulsation and the development of dementia in Parkinson's disease (PD) patients using EPI-based fMRI. Methods: We measured CSF pulsation in the 4th ventricle of 17 healthy controls and 35 PD patients using a novel CSF pulsation index termed "CSFpulse" based on echo-planar imaging (EPI)-based fMRI. The PD patients were classified into a PD with dementia high-risk group (PDD-H, n = 19) and a low risk group (PDD-L, n = 16), depending on their development of dementia within 5 years after initial brain imaging. The size of the 4th ventricle was measured using intensity-based thresholding. Results: We found that CSF pulsation was significantly higher in PD patients than in healthy controls, and that PD patients with high risk of dementia (PDD-H) had the highest CSF pulsation. We also observed an enlargement of the 4th ventricle in PD patients compared to healthy controls. Conclusion: Our results suggest that CSF pulsation may be a potential biomarker for PD progression and cognitive decline, and that EPI-based fMRI can be a useful tool for studying CSF flow and brain function in PD.

Unsupervised machine learning for clustering forward head posture, protraction and retraction movement patterns based on craniocervical angle data in individuals with nonspecific neck pain.

OBJECTIVES: The traditional understanding of craniocervical alignment emphasizes specific anatomical landmarks. However, recent research has challenged the reliance on forward head posture as the primary diagnostic criterion for neck pain. An advanced relationship exists between neck pain and craniocervical alignment, which requires a deeper exploration of diverse postures and movement patterns using advanced techniques, such as clustering analysis. We aimed to explore the complex relationship between craniocervical alignment, and neck pain and to categorize alignment patterns in individuals with nonspecific neck pain using the K-means algorithm. METHODS: This study included 229 office workers with nonspecific neck pain who applied unsupervised machine learning techniques. The craniocervical angles (CCA) during rest, protraction, and retraction were measured using two-dimensional video analysis, and neck pain severity was assessed using the Northwick Park Neck Pain Questionnaire (NPQ). CCA during sitting upright in a comfortable position was assessed to evaluate the resting CCA. The average of midpoints between repeated protraction and retraction measures was considered as the midpoint CCA. The K-means algorithm helped categorize participants into alignment clusters based on age, sex and CCA data. RESULTS: We found no significant correlation between NPQ scores and CCA data, challenging the traditional understanding of neck pain and alignment. We observed a significant difference in age (F = 140.14, p < 0.001), NPQ total score (F = 115.83, p < 0.001), resting CCA (F = 79.22, p < 0.001), CCA during protraction (F = 33.98, p < 0.001), CCA during retraction (F = 40.40, p < 0.001), and midpoint CCA (F = 66.92, p < 0.001) among the three clusters and healthy controls. Cluster 1 was characterized by the lowest resting and midpoint CCA, and CCA during pro- and -retraction, indicating a significant forward head posture and a pattern of retraction restriction. Cluster 2, the oldest group, showed CCA measurements similar to healthy controls, yet reported the highest NPQ scores. Cluster 3 exhibited the highest CCA during protraction and retraction, suggesting a limitation in protraction movement. DISCUSSION: Analyzing 229 office workers, three distinct alignment patterns were identified, each with unique postural characteristics; therefore, treatments addressing posture should be individualized and not generalized across the population.

Scn2a deletion disrupts oligodendroglia function: Implication for myelination, neural circuitry, and auditory hypersensitivity in ASD.

Autism spectrum disorder (ASD) is characterized by a complex etiology, with genetic determinants significantly influencing its manifestation. Among these, the Scn2a gene emerges as a pivotal player, crucially involved in both glial and neuronal functionality. This study elucidates the underexplored roles of Scn2a in oligodendrocytes, and its subsequent impact on myelination and auditory neural processes. The results reveal a nuanced interplay between oligodendrocytes and axons, where Scn2a deletion causes alterations in the intricate process of myelination. This disruption, in turn, instigates changes in axonal properties and neuronal activities at the single cell level. Furthermore, oligodendrocyte-specific Scn2a deletion compromises the integrity of neural circuitry within auditory pathways, leading to auditory hypersensitivity-a common sensory abnormality observed in ASD. Through transcriptional profiling, we identified alterations in the expression of myelin-associated genes, highlighting the cellular consequences engendered by Scn2a deletion. In summary, the findings provide unprecedented insights into the pathway from Scn2a deletion in oligodendrocytes to sensory abnormalities in ASD, underscoring the integral role of Scn2a -mediated myelination in auditory responses. This research thereby provides novel insights into the intricate tapestry of genetic and cellular interactions inherent in ASD.

Machine learning models for classifying non-specific neck pain using craniocervical posture and movement.

OBJECTIVE: Physical therapists and clinicians commonly confirm craniocervical posture (CCP), cervical retraction, and craniocervical flexion as screening tests because they contribute to non-specific neck pain (NSNP). We compared the predictive performance of statistical machine learning (ML) models for classifying individuals with and without NSNP using datasets containing CCP and cervical kinematics during pro- and retraction (CKdPR). DESIGN: Exploratory, cross-sectional design. SETTING AND PARTICIPANTS: In total, 773 public service office workers (PSOWs) were screened for eligibility (NSNP, 441; without NSNP, 332). METHODS: We set up five datasets (CCP, cervical kinematics during the protraction, cervical kinematics during the retraction, CKdPR and combination of the CCP and CKdPR). Four ML algorithms-random forest, logistic regression, Extreme Gradient boosting, and support vector machine-were trained. MAIN OUTCOME MEASURES: Model performance were assessed using area under the curve (AUC), accuracy, precision, recall and F1-score. To interpret the predictions, we used Feature permutation importance and SHapley Additive explanation values. RESULTS: The random forest model in the CKdPR dataset classified PSOWs with and without NSNP and achieved the best AUC among the five datasets using the test data (AUC, 0.892 [good]; F1, 0.832). The random forest model in the CCP dataset had the worst AUC among the five datasets using the test data [AUC, 0.738 (fair); F1, 0.715]. CONCLUSION: ML performance was higher for the CKdPR dataset than for the CCP dataset, suggesting that ML algorithms are more suitable than classical statistical methods for developing robust models for classifying PSOWs with and without NSNP.

Geometry-driven self-supervision for 3D human pose estimation.

Although 3D human pose estimation has recently made strides, it is still difficult to precisely recreate a 3D human posture from a single image without the aid of 3D annotation for the following reasons. Firstly, the process of reconstruction inherently suffers from ambiguity, as multiple 3D poses can be projected onto the same 2D pose. Secondly, accurately measuring camera rotation without laborious camera calibration is a difficult task. While some approaches attempt to address these issues using traditional computer vision algorithms, they are not differentiable and cannot be optimized through training. This paper introduces two modules that explicitly leverage geometry to overcome these challenges, without requiring any 3D ground-truth or camera parameters. The first module, known as the relative depth estimation module, effectively mitigates depth ambiguity by narrowing down the possible depths for each joint to only two candidates. The second module, referred to as the differentiable pose alignment module, calculates camera rotation by aligning poses from different views. The use of these geometrically interpretable modules reduces the complexity of training and yields superior performance. By adopting our proposed method, we achieve state-of-the-art results on standard benchmark datasets, surpassing other self-supervised methods and even outperforming several fully-supervised approaches that heavily rely on 3D annotations.

Classification of chronic ankle instability using machine learning technique based on ankle kinematics during heel rise in delivery workers.

Objective: Ankle injuries in delivery workers (DWs) are often caused by trips, and high recurrence rates of ankle sprains are related to chronic ankle instability (CAI). Heel rise requires joint angles and moments similar to those of the terminal stance phase of walking that the foot supinates. Thus, our study aimed to develop, determine, and compare the predictive performance of statistical machine learning models to classify DWs with and without CAI using ankle kinematics during heel rise. Methods: In total, 203 DWs were screened for eligibility. Seven predictors were included in our study (age, work duration, body mass index, calcaneal stance position angle [CSPA] in the initial and terminal positions during heel rise, calcaneal movement during heel rise [CMHR], and plantar flexion angle during heel rise). Six machine learning algorithms, including logistic regression, decision tree, AdaBoost, Extreme Gradient boosting machines, random forest, and support vector machine, were trained. Results: The random forest model (area under the curve [AUC], 0.967 [excellent]; F1, 0.889; accuracy, 0.925) confirmed the best predictive performance in the test datasets among the six machine learning models. For Shapley Additive Explanations, old age, low CMHR, high CSPA in the initial position, high PFA, long work duration, low CSPA in the terminal position, and high body mass index were the most important predictors of CAI in the random forest model. Conclusion: Ankle kinematics during heel rise can be considered in the classification of DWs with and without CAI.

Measurement of changes in cerebrospinal fluid pulsation after traumatic brain injury using echo-planar imaging-based functional MRI.

Traumatic brain injury (TBI) is a major public health concern worldwide, with a high incidence and a significant impact on morbidity and mortality. The alteration of cerebrospinal fluid (CSF) dynamics after TBI is a well-known phenomenon; however, the underlying mechanisms and their implications for cognitive function are not fully understood. In this study, we propose a new approach to studying the alteration of CSF dynamics in TBI patients. Our approach involves using conventional echo-planar imaging-based functional MRI with no additional scan, allowing for simultaneous assessment of functional CSF dynamics and blood oxygen level-dependent-based functional brain activities. We utilized two previously suggested indices of (i) CSFpulse, and (ii) correlation between global brain activity and CSF inflow. Using CSFpulse, we demonstrated a significant decrease in CSF pulsation following TBI (p < 0.05), which was consistent with previous studies. Furthermore, we confirmed that the decrease in CSF pulsation was most prominent in the early months after TBI, which could be explained by ependymal ciliary loss, intracranial pressure increment, or aquaporin-4 dysregulation. We also observed a decreasing trend in the correlation between global brain activity and CSF inflow in TBI patients (p < 0.05). Our findings suggest that the decreased CSF pulsation after TBI could lead to the accumulation of toxic substances in the brain and an adverse effect on brain function. Further longitudinal studies with larger sample sizes, TBI biomarker data, and various demographic information are needed to investigate the association between cognitive decline and CSF dynamics after TBI. Overall, this study sheds light on the potential role of altered CSF dynamics in TBI-induced neurologic symptoms and may contribute to the development of novel therapeutic interventions.

Prediction model of subacromial pain syndrome in assembly workers using shoulder range of motion and muscle strength based on support vector machine.

Subacromial pain syndrome (SAPS) is the most common upper-extremity musculoskeletal problem among workers. In this study, a machine learning model was built to predict and classify the presence or absence of SAPS in assembly workers with shoulder joint range of motion (ROM) and muscle strength data using support vector machine (SVM). Permutation importance was used to determine important variables for predicting workers with or without SAPS. The accuracy of the support vector classifier (SVC) polynomial model for classifying workers with SAPS was 82.4%. The important variables in model construction were internal rotation and abduction of shoulder ROM and internal rotation of shoulder muscle strength. It is possible to accurately perform SAPS classification of workers with relatively easy-to-obtain shoulder ROM and muscle strength data using this model. In addition, preventing SAPS in workers is possible by adjusting the factors affecting model building using exercise or rehabilitation programs.Practitioner summary: This study aimed to create a machine learning model that can predict and classify SAPS using shoulder ROM and muscle strength and identify the variables that are of high importance in model construction. This model could be used to predict or classify workers' SAPS and manage or prevent SAPS.

Gastrodia elata rhizoma ameliorates thioacetamide-induced liver injury in dogs.

Objective: The study aimed to investigate the hepatoprotective effects of Gastrodia elata rhizome (GR) on thioacetamide (TAA)-induced liver injury in dogs. We evaluated serum biochemical and hematological parameters, with emphasis on alanine transaminase (ALT), alanine phosphates (ALP), and nitric oxide (NO) levels, in dogs with TAA-induced liver injury. Materials and Methods: The animals were divided into a control group (Con), TAA group, Silymarin group (Sil, 50 mg/kg), Gastrodia rhizome low dose (GRL) (low) + TAA, GRH (high) + TAA, and GR high-dose group (GRH) control group. GRL and GRH were given daily at 50 and 100 mg/kg, respectively. TAA was given on days 1, 4, and 7 at a dose of 300 mg/kg. Results: GR significantly reduced liver injury in treated animals, as indicated by lowered levels of ALT (about 32% at day 21 in both GRL + TAA and GRH + TAA groups), ALP (about 17% and 21% at day 21 in both GRL + TAA, GRH + TAA groups, respectively), and NO (about 36% at day 21 in both GRL + TAA, GRH + TAA groups) compared to the TAA control group. Hematological parameters showed mild changes during the experiment. High-performance liquid chromatography analysis revealed gastrodin, a major component of the GR extract, constitutes 2.6% of the extract. Conclusion: The GR demonstrated significant hepatoprotective effects against TAA-induced liver injury in dogs. The study provides evidence for the potential therapeutic use of GR in the management of liver diseases.

Autophagy collaborates with apoptosis pathways to control oligodendrocyte number.

Oligodendrocytes are the sole myelin-producing cells in the central nervous system. Oligodendrocyte number is tightly controlled across diverse brain regions to match local axon type and number, yet the underlying mechanisms remain unclear. Here, we show that autophagy, an evolutionarily conserved cellular process that promotes cell survival under physiological conditions, elicits premyelinating oligodendrocyte apoptosis during development. Autophagy flux is increased in premyelinating oligodendrocytes, and its genetic blockage causes ectopic oligodendrocyte survival throughout the entire brain. Autophagy functions cell autonomously in the premyelinating oligodendrocyte to trigger cell apoptosis, and it genetically interacts with the TFEB pathway to limit oligodendrocyte number across diverse brain regions. Our results provide in vivo evidence showing that autophagy promotes apoptosis in mammalian cells under physiological conditions and reveal key intrinsic mechanisms governing oligodendrogenesis.

Heterogeneous complement and microglia activation mediates stress-induced synapse loss.

Spatially heterogeneous synapse loss is a characteristic of many psychiatric and neurological disorders, but the underlying mechanisms are unclear. Here, we show that spatially-restricted complement activation mediates stress-induced heterogeneous microglia activation and synapse loss localized to the upper layers of the mouse medial prefrontal cortex (mPFC). Single cell RNA sequencing also reveals a stress-associated microglia state marked by high expression of the apolipoprotein E gene (ApoE high ) localized to the upper layers of the mPFC. Mice lacking complement component C3 are protected from stress-induced layer-specific synapse loss, and the ApoE high microglia population is markedly reduced in the mPFC of these mice. Furthermore, C3 knockout mice are also resilient to stress-induced anhedonia and working memory behavioral deficits. Our findings suggest that region-specific complement and microglia activation can contribute to the disease-specific spatially restricted patterns of synapse loss and clinical symptoms found in many brain diseases.

Non-invasive flow mapping of parasagittal meningeal lymphatics using 2D interslice flow saturation MRI.

The clearance pathways of brain waste products in humans are still under debate in part due to the lack of noninvasive imaging techniques for meningeal lymphatic vessels (mLVs). In this study, we propose a new noninvasive mLVs imaging technique based on an inter-slice blood perfusion MRI called alternate ascending/descending directional navigation (ALADDIN). ALADDIN with inversion recovery (IR) at single inversion time of 2300 ms (single-TI IR-ALADDIN) clearly demonstrated parasagittal mLVs around the human superior sagittal sinus (SSS) with better detectability and specificity than the previously suggested noninvasive imaging techniques. While in many studies it has been difficult to detect mLVs and confirm their signal source noninvasively, the detection of mLVs in this study was confirmed by their posterior to anterior flow direction and their velocities and morphological features, which were consistent with those from the literature. In addition, IR-ALADDIN was compared with contrast-enhanced black blood imaging to confirm the detection of mLVs and its similarity. For the quantification of flow velocity of mLVs, IR-ALADDIN was performed at three inversion times of 2000, 2300, and 2600 ms (three-TI IR-ALADDIN) for both a flow phantom and humans. For this preliminary result, the flow velocity of the dorsal mLVs in humans ranged between 2.2 and 2.7 mm/s. Overall, (i) the single-TI IR-ALADDIN can be used as a novel non-invasive method to visualize mLVs in the whole brain with scan time of ~ 17 min and (ii) the multi-TI IR-ALADDIN can be used as a way to quantify the flow velocity of mLVs with a scan time of ~ 10 min (or shorter) in a limited coverage. Accordingly, the suggested approach can be applied to noninvasively studying meningeal lymphatic flows in general and also understanding the clearance pathways of waste production through mLVs in humans, which warrants further investigation.

Autophagy collaborates with apoptosis pathways to control myelination specificity and function.

Oligodendrocytes are the sole myelin producing cells in the central nervous system. Oligodendrocyte numbers are tightly controlled across diverse brain regions to match local axon type and number, but the underlying mechanisms and functional significance remain unclear. Here, we show that autophagy, an evolutionarily conserved cellular process that promotes cell survival under canonical settings, elicits premyelinating oligodendrocyte apoptosis during development and regulates critical aspects of nerve pulse propagation. Autophagy flux is increased in premyelinating oligodendrocytes, and its genetic blockage causes ectopic oligodendrocyte survival throughout the entire brain. Autophagy acts in the TFEB-Bax/Bak pathway and elevates PUMA mRNA levels to trigger premyelinating oligodendrocyte apoptosis cell-autonomously. Autophagy continuously functions in the myelinating oligodendrocytes to limit myelin sheath numbers and fine-tune nerve pulse propagation. Our results provide in vivo evidence showing that autophagy promotes apoptosis in mammalian cells under physiological conditions and reveal key intrinsic mechanisms governing oligodendrocyte number. HIGHLIGHTS: Autophagy flux increases in the premyelinating and myelinating oligodendrocytesAutophagy promotes premyelinating oligodendrocyte (pre-OL) apoptosis to control myelination location and timing Autophagy acts in the TFEB-PUMA-Bax/Bak pathway and elevates PUMA mRNA levels to determine pre-OL fate Autophagy continuously functions in the myelinating oligodendrocytes to limit myelin sheath thickness and finetune nerve pulse propagation.

Comparison of shoulder functions between assembly workers with and without subacromial pain syndrome.

BACKGROUND: The occurrence of subacromial pain syndrome (SPS) is associated with the frequent handling and lifting of heavy loads and excessive repetitive work. Thus, assembly workers have a high prevalence of SPS. OBJECTIVE: The purpose of this study was to investigate differences in shoulder ROM, muscle strength, asymmetry ratio, function, productivity, and depression between workers with and without SPS. METHODS: Sixty-seven male workers (35 workers with SPS and 32 workers without SPS) participated in this study. Shoulder internal rotation (SIR), shoulder external rotation (SER), shoulder abduction (SAB), shoulder horizontal adduction ROM and SIR, SER, elbow flexion (EF), scapular depression and adduction, scapular protraction strength were measured. The asymmetry ratio was calculated using the asymmetry ratio formula; shoulder functions were measured using the shoulder pain and disability index (SPADI), disabilities of the arm, shoulder, and hand (DASH), and visual analogue scale (VAS); and Endicott work productivity scale (EWPS). RESULTS: The SPADI (p = 0.001), DASH (p = 0.001), and VAS (p = 0.001) values of workers with SPS were higher than those of workers without SPS. Also, workers with SPS had lower SIR (p = 0.001) and SAB (p = 0.002) ROM compared to workers without SPS. In addition, workers with SPS exhibited lower SIR (p = 0.012) strength than workers without SPS. Workers with SPS had higher asymmetry ratio in SIR (p = 0.015), SER (p = 0.005), and EF (p = 0.008) strength than workers without SPS. CONCLUSIONS: The SIR, SAB ROM, SIR strength, and the asymmetry ratio of SIR, SER, EF strengths could provide an important baseline comparison for the workers with SPS.

Enhancement of TRP Gene Expression and UV Absorption by Bioconverted Chestnut Inner Shell Extracts Using Lactiplantibacillus plantarum.

In this work, the suppression of tyrosinase-related genes, including an improvement in UV absorption effects of bioconverted CS extracts (BCS), was investigated to improve the skin-whitening effect. Total polyphenols and total flavonoids, which are bioactive components, increased 2.6- and 5.4-times in bioconversion using Lactiplantibacillus plantarum SM4, respectively, as compared to ultrasound-assisted extracts (UCS). The effect of BCS on radical scavenging activity, UV-A absorption, and tyrosinase activity inhibition, contributing to skin-whitening, were 1.3-, 1.2-, and 1.2-times higher than those of UCS, respectively. The main component identified in high-performance liquid chromatography (HPLC) was gallic acid in both UCS and BCS, which increased by 2.9-times following bioconversion. The gene expression of tyrosinase-related proteins, including TRP-1 and TRP-2 genes, was studied to confirm the suppression of melanin synthesis by BCS in order to identify the skin-whitening mechanism, and BCS decreased both genes' expression by 1.7- and 1.6-times, demonstrating that BCS effectively suppressed melanin synthesis. These findings imply that the chestnut inner shell can be employed as a cosmetic material by simultaneously inhibiting melanogenesis and enhancing UV-A absorption through bioconversion using L. plantarum SM4.

Effect of improved thoracic kyphosis on forward shoulder posture after mobilization in individuals with thoracic hyperkyphosis.

BACKGROUND: Thoracic hyperkyphosis structurally alters the position of the scapula to cause forward shoulder posture. However, the effect of improved thoracic hyperkyphosis on forward shoulder posture is unclear. The objective of this study was to determine the effect of eight weeks of thoracic mobilization on improving thoracic hyperkyphosis and forward shoulder posture and determine the cutoff change ratio in kyphosis for improving forward shoulder posture using the decision tree method. METHOD: This study included 19 participants with thoracic hyperkyphosis who underwent thoracic mobilization for eight weeks. Forward shoulder posture (acromion-to-the-wall index) and thoracic kyphosis were measured before and after thoracic mobilization. FINDINGS: The intervention significantly improved thoracic kyphosis and forward shoulder posture. The cutoff change ratio in kyphosis for improving forward shoulder posture was >13.79%. In the subgroup analysis of participants with a change ratio of kyphosis >13.79% (seven cases), all patients showed improved forward shoulder posture. In contrast, in the subgroup with a change ratio of kyphosis ≤13.79% (12 cases), eight cases showed improved forward shoulder posture, while four cases showed no improvement. INTERPRETATION: Thoracic mobilization can be recommended in shoulder rehabilitation programs to improve forward shoulder posture to manage and prevent scapular malalignment in individuals with thoracic hyperkyphosis. We suggest that a high probability of improvement in forward shoulder posture can be expected when kyphosis is improved by >13.79%.

Measurement of CSF pulsation from EPI-based human fMRI.

It is recently discovered that the glymphatic system and meningeal lymphatic system are the primary routes for the clearance of brain waste products. The CSF flow is part of these systems, facilitating the clearance procedure. Nonetheless, the relationship between CSF flow and brain functional activity has been underexplored. To investigate CSF dynamics and functional brain activity simultaneously, recent studies have proposed a CSF inflow index measured on edge slices (CSFedge) of echo-planar imaging (EPI) based functional magnetic resonance imaging (fMRI), however, it lacks the quantitative aspect of the CSF pulsation. We proposed a new method for quantifying CSF pulsation (CSFpulse) based on an interslice CSF pulsation model in the 4th ventricle of EPI-based fMRI. The proposed CSFpulse successfully detected the higher CSF flow during the resting state than the typical task states (visual and motor) (p<.05), which is consistent with previous studies based on phase contrast (PC) MRI and CSF volume MRI, while it was not detected in CSFedge based indices or baseline CSF signals in various regions of interest (ROIs). Moreover, CSFpulse demonstrated dynamic functional changes in CSF pulsation: it decreased during the activation-on blocks while it increased during the activation-off blocks. CSFpulse significantly correlated with stroke volume measured using PC MRI, a standard method for CSF pulsation quantification, under the same functional state, while CSFedge based indices or CSF ROIs showed no correlation with the PC MRI stroke volume. Lastly, the correlation of CSFpulse with global BOLD was weaker than that of CSFedge, suggesting that CSFpulse may reflect distinct CSF physiological information that is less affected by global BOLD effects. Based on these results, the proposed CSFpulse provides CSF pulsatility information more accurately in a quantitative manner than CSFedge based indices from the recent CSF studies or the conventional ROI-based analysis. In addition to the high correlation with PC MRI, CSFpulse is much faster than PC MRI and provides information of functional brain activations simultaneously, advantageous over PC MRI or CSF volume MRI. Accordingly, the suggested CSFpulse can be used for investigating intra-subject functional changes in BOLD and CSF pulsation simultaneously and inter-subject CSF pulsation variations based on conventional EPI-based fMRI, which warrants further investigation.

Loss of ß4-spectrin impairs Nav channel clustering at the heminode and temporal fidelity of presynaptic spikes in developing auditory brain.

Beta-4 (ß4)-spectrin, encoded by the gene Sptbn4, is a cytoskeleton protein found at nodes and the axon initial segments (AIS). Sptbn4 mutations are associated with myopathy, neuropathy, and auditory deficits in humans. Related to auditory dysfunction, however, the expression and roles of ß4-spectrin at axon segments along the myelinated axon in the developing auditory brain are not well explored. We found during postnatal development, ß4-spectrin is critical for voltage-gated sodium channel (Nav) clustering at the heminode along the nerve terminal, but not for the formation of nodal and AIS structures in the auditory brainstem. Presynaptic terminal recordings in Sptbn4geo mice, ß4-spectrin null mice, showed an elevated threshold of action potential and increased failures during action potential train at high-frequency. Sptbn4geo mice exhibited a slower central conduction and showed no startle responses, but had normal cochlear function. Taken together, the lack of ß4-spectrin impairs Nav clustering at the heminode along the nerve terminal and the temporal fidelity and reliability of presynaptic spikes, leading to central auditory processing deficits during postnatal development.