Effects of computerized working memory training on neuroplasticity in healthy individuals: A combined neuroimaging and neurotransmitter study.

Working memory (WM) is an essential cognitive function that underpins various higher-order cognitive processes. Improving WM capacity through targeted training interventions has emergered as a potential approach for enhancing cognitive abilities. The present study employed an 8-week regimen of computerized WM training (WMT) to investigate its effect on neuroplasticity in healthy individuals, utilizing neuroimaging data gathered both before and after the training. The key metrics assessed included the amplitude of low-frequency fluctuations (ALFF), voxel-based morphometry (VBM), and the spatial distribution correlations of neurotransmitter. The results indicated that post-training, compared to baseline, there was a reduction in ALFF in the medial superior frontal gyrus and an elevation in ALFF in the left middle occipital gyrus within the training group. In comparison to the control group, the training group also exhibited decreased ALFF in the anterior cingulate cortex, angular gyrus, and superior parietal lobule, along with increased ALFF in the postcentral gyrus post-training. VBM analysis revealed a significant increase in gray matter volume (GMV) in the right dorsal superior frontal gyrus after the training period, compared to the initial baseline measurement. Furthermore, the training group showed GMV increases in the dorsal superior frontal gyrus, Rolandic operculum, precentral gyrus, and postcentral gyrus when compared to the control group. In addition, significant associations were identifed between neuroimaging measurements (AFLL and VBM) and the spatial patterns of neurotransmitters such as serotonin (5-HT), dopamine (DA), and N-methyl-D-aspartate (NMDA), providing insights into the underlying neurochemical processes. These findings clarify the neuroplastic changes caused by WMT, offering a deeper understanding of brain plasticity and highlighting the potential advantages of cognitive training interventions.

Rhein targets macrophage SIRT2 to promote adipose tissue thermogenesis in obesity in mice.

Rhein, a component derived from rhubarb, has been proven to possess anti-inflammatory properties. Here, we show that rhein mitigates obesity by promoting adipose tissue thermogenesis in diet-induced obese mice. We construct a macrophage-adipocyte co-culture system and demonstrate that rhein promotes adipocyte thermogenesis through inhibiting NLRP3 inflammasome activation in macrophages. Moreover, clues from acetylome analysis identify SIRT2 as a potential drug target of rhein. We further verify that rhein directly interacts with SIRT2 and inhibits NLRP3 inflammasome activation in a SIRT2-dependent way. Myeloid knockdown of SIRT2 abrogates adipose tissue thermogenesis and metabolic benefits in obese mice induced by rhein. Together, our findings elucidate that rhein inhibits NLRP3 inflammasome activation in macrophages by regulating SIRT2, and thus promotes white adipose tissue thermogenesis during obesity. These findings uncover the molecular mechanism underlying the anti-inflammatory and anti-obesity effects of rhein, and suggest that rhein may become a potential drug for treating obesity.

Analysis of factors influencing medical students' learning engagement and its implications for teaching work-- a network analysis perspective.

PURPOSE: Higher medical education has always been a major project in the fields of education and health, and therefore, the quality of education has received much attention. Learning engagement has emerged as a significant indicator of teaching quality, attracting considerable research attention. This study aims to explore the relationship between medical students' learning engagement and their sense of school belonging, professional identity, and academic self-efficacy. METHODS: We conducted an online survey using convenience sampling method with 311 medical students. We employed Revised version of the Utrech Work Engagement Scale-Student (UWES-S), Chinese version of the Psychological Sense of School Membership (PSSM) scale, Academic Self-Efficacy Scale, and the questionnaire of college students' speciality identity for evaluation. Network analysis was used to analyze the relationships among these factors. RESULTS: Medical students' overall performance in school showed a positive trend. However, there is still room for improvement. In the network structure of learning engagement and its influencing factors, the "emotional" aspect of professional identity (EI = 1.11) was considered to be an important node with strong centrality. And "academic competence self-efficacy" aspect of academic self-efficacy (BEI = 0.72) was considered an important node with strong transitivity. CONCLUSION: Deepening medical students' emotional identification with their profession and enhancing their confidence in their academic abilities may improve their learning engagement and educational quality.

Assessment of TENS-Evoked Tactile Sensations for Transradial Amputees via EEG Investigation.

Most of current prostheses can offer motor function restoration for limb amputees but usually lack natural and intuitive sensory feedback. Many studies have demonstrated that Transcutaneous Electrical Nerve Stimulation (TENS) is promising in non-invasive sensation evoking for amputees. However, the objective evaluation and mechanism analysis on sensation feedback are still limited. This work utilized multi-channel TENS with diverse stimulus patterns to evoke sensations on four non-disabled subjects and two transradial amputees. Meanwhile, electroencephalogram (EEG) was collected to objectively assess the evoked sensations, where event-related potentials (ERPs), brain electrical activity maps (BEAMs), and functional connectivity (FC) were computed. The results show that various sensations could be successfully evoked for both amputees and non-disabled subjects by customizing stimulus parameters. The ERP confirmed the sensation and revealed the sensory-processing-related components like N100 and P200; the BEAMs confirmed the corresponding regions of somatosensory cortex were activated by stimulation; the FC indicated an increase of interactions between the regions of sensorimotor cortex. This study may shed light on how the brain responds to external stimulation as sensory feedback and serve as a pilot for further bidirectional closed-loop prosthetic control.

Preoperative prediction of microvascular invasion risk in hepatocellular carcinoma with MRI: peritumoral versus tumor region.

OBJECTIVES: To explore the predictive performance of tumor and multiple peritumoral regions on dynamic contrast-enhanced magnetic resonance imaging (MRI), to identify optimal regions of interest for developing a preoperative predictive model for the grade of microvascular invasion (MVI). METHODS: A total of 147 patients who were surgically diagnosed with hepatocellular carcinoma, and had a maximum tumor diameter ≤ 5 cm were recruited and subsequently divided into a training set (n = 117) and a testing set (n = 30) based on the date of surgery. We utilized a pre-trained AlexNet to extract deep learning features from seven different regions of the maximum transverse cross-section of tumors in various MRI sequence images. Subsequently, an extreme gradient boosting (XGBoost) classifier was employed to construct the MVI grade prediction model, with evaluation based on the area under the curve (AUC). RESULTS: The XGBoost classifier trained with data from the 20-mm peritumoral region showed superior AUC compared to the tumor region alone. AUC values consistently increased when utilizing data from 5-mm, 10-mm, and 20-mm peritumoral regions. Combining arterial and delayed-phase data yielded the highest predictive performance, with micro- and macro-average AUCs of 0.78 and 0.74, respectively. Integration of clinical data further improved AUCs values to 0.83 and 0.80. CONCLUSION: Compared with those of the tumor region, the deep learning features of the peritumoral region provide more important information for predicting the grade of MVI. Combining the tumor region and the 20-mm peritumoral region resulted in a relatively ideal and accurate region within which the grade of MVI can be predicted. CLINICAL RELEVANCE STATEMENT: The 20-mm peritumoral region holds more significance than the tumor region in predicting MVI grade. Deep learning features can indirectly predict MVI by extracting information from the tumor region and directly capturing MVI information from the peritumoral region. KEY POINTS: We investigated tumor and different peritumoral regions, as well as their fusion. MVI predominantly occurs in the peritumoral region, a superior predictor compared to the tumor region. The peritumoral 20 mm region is reasonable for accurately predicting the three-grade MVI.

Targeting HMGCS1 restores chemotherapy sensitivity in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a common hematological malignancy with overall poor prognosis. Exploring novel targets is urgent and necessary to improve the clinical outcome of relapsed and refractory (RR) AML patients. Through clinical specimens, animal models and cell-level studies, we explored the specific mechanism of 3-hydroxy-3-methylglutaryl coenzyme A synthase 1 (HMGCS1) in AML and the mechanism of targeting HMGCS1 to attenuate cell proliferation, increase chemotherapy sensitivity and improve the occurrence and development of AML. Here, we reveal that HMGCS1 is overexpressed in RR patients and negatively related to overall survival (OS). Knocking out HMGCS1 in AML cells attenuated cell proliferation and increased chemotherapy sensitivity, while stable overexpression of HMGCS1 had the opposite effects. Mechanistically, we identified that knockout of HMGCS1 suppressed mitogen-activated protein kinase (MAPK) pathway activity, while overexpression of HMGCS1 could remarkably enhance the pathway. U0126, a MEK1 inhibitor, offset the effects of HMGCS1 overexpression, indicating that HMGCS1 promotes RR AML through the MAPK pathway. Further, we verified that hymeglusin, a specific inhibitor of HMGCS1, decreases cell growth both in AML cell lines and primary bone marrow cells of AML patients. Furthermore, combination of hymeglusin and the common chemotherapeutic drug cytarabine and adriamycin (ADR) had synergistic toxic effects on AML cells. Our study demonstrates the important role of HMGCS1 in AML, and targeting this protein is promising for the treatment of RR AML.

Microneedle Array Electrodes Fabricated With 3D Printing Technology for High-Quality Electrophysiological Acquisition.

Electrophysiological recordings are vital in assessing biological functions, diagnosing diseases, and facilitating biofeedback and rehabilitation. The applications of conventional wet (gel) electrodes often come with some limitations. Microneedle array electrodes (MAEs) present a possible solution for high-quality electrophysiological acquisition, while the prior technologies for MAE fabrication have been either complex, expensive, or incapable of producing microneedles with uniform dimensions. This work employed a projection stereolithography (P µ SL) 3D printing technology to fabricate MAEs with micrometer-level precision. The MAEs were compared with gel and flat electrodes on electrode-skin interface impedance (EII) and performances of EMG and ECG acquisition. The experimental results indicate that the P µ SL 3D printing technology contributed to an easy-to-perform and low-cost fabrication approach for MAEs. The developed MAEs exhibited promising EII and enabled a stable EMG and ECG acquisition in different conditions without inducing skin allergies, inflammation, or injuries. This research lies in the development of a type of customizable MAE with considerable biomedical application potentials for ultra-minimally invasive or non-invasive electrophysiological acquisition.

Comparing clinical outcomes of patients with severe lower limb trauma undergoing orthoplastic and orthopedic surgeries: A long-term study protocol.

This long-term study protocol aims to compare the clinical outcomes of patients with severe lower limb trauma undergoing orthoplastic and orthopedic surgeries, focusing on their physical and psychological status. Patients with lower limb injuries and open fractures have been recruited since October 2019 and will be followed up until October 2024. The patients will be divided into two groups: (1) Orthoplastic group, where single-stage debridement, fixation, and soft tissue repair will be performed, and (2) Orthopedic group, where soft tissue repair will be done in a delayed-stage. The follow-up period will be one year, during which clinical data, limb function recovery, psychological scores, and health-related quality of life (HRQOL) will be evaluated to assess postoperative recovery and clinical outcomes. Additional clinical data, such as socio-demographic information, baseline features, Enneking score, Visual Analogue Scale (VAS) score, two-point discrimination score, and blood test parameters will also be collected. The 36-Item Short Form Health Survey (SF-36) will be used to evaluate HRQOL, while the Post-traumatic Stress Disorder Checklist (PCL) will assess the severity of self-reported post-traumatic stress disorder. The results of this study will provide valuable insights into prognostically relevant targets and contribute to improving the management and outcomes of patients with lower limb injuries and open fractures, who often face challenges related to limb disability and potential amputation postoperatively, significantly impacting their psychological and physical well-being.

Development and validation of bioanalytical assays for the quantification of 9MW2821, a nectin-4-targeting antibody-drug conjugate.

We designed and developed 9MW2821, an anti-Nectin-4 antibody-drug conjugate (ADC) with an enzymatically cleavable valine-citrulline linker and monomethyl auristatin E (MMAE) as the payload. Four bioanalytical assays for total antibodies, conjugated antibodies, conjugated payload, and free payload were then developed and validated for the comprehensive evaluation of the multiple drug forms of 9MW2821. Specific sandwich enzyme-linked immunosorbent assays were used to quantify total antibodies and conjugated antibody, showing good drug-to-antibody ratio (DAR) tolerance. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to determine free MMAE, and conjugated MMAE was quantified using a combination of ligand-binding assay (LBA) and LC-MS/MS. Based on these four assays, we studied the serum stability and monkey pharmacokinetic profiles of 9MW2821, and the in vivo DAR of 9MW2821 was calculated and dynamically monitored. In conclusion, we developed and validated series of bioanalytical assays to quantify multiple forms of 9MW2821, a new ADC, and used the assays to evaluate the serum stability and monkey pharmacokinetic characteristics. The results indicate good linker stability and suggest that the developed assays can be further used in clinical settings.

A novel mechanism behind irreversible development of cartilage degradation driven articular cartilage defects revealed by rat model: The chain reaction initiated by extracellular vesicles delivered LOC102546541.

BACKGROUND: Articular cartilage defects (ACD) are injuries with a diameter greater than 3 mm, resulting from wear and tear on joints. When the diameter of the defect exceeds 6 mm, it can further damage the surrounding joint cartilage, causing osteoarthritis (OA). Try to explain why OA is an irreversible disease, we hypothesize that damaged articular chondrocytes (DAC) may have reduced capacities to repair cartilage because its extracellular vesicle (EVs) that might directly contribute to OA formation. METHODS: In this study, DAC-EVs and AC-EVs were isolated using ultracentrifugation. Next-generation sequencing was employed to screen for a pathogenic long non-coding RNA (lncRNA). After verifying its function in vitro, the corresponding small interfering RNA (siRNA) was constructed and loaded into extracellular vesicles, which were then injected into the knee joint cavities of rats. RESULTS: The results revealed that DAC-EVs packaged lncRNA LOC102546541 acts as a competitive endogenous RNA (ceRNA) of MMP13, down-regulating miR-632. Consequently, the function of MMP13 in degrading the extracellular matrix is enhanced, promoting the development of osteoarthritis. CONCLUSIONS: This study uncovered a novel mode of OA pathogenesis using rat models, which DAC deliver pathogenic LOC102546541 packaged EVs to normal articular chondrocytes, amplifying the degradation of the extracellular matrix. Nonetheless, the functions of highly homologous human gene of LOC102546541 need to be verified in the future.

The efficacy of low frequency repetitive transcial magnetic stimulation for treating auditory verbal hallucinations in schizophrenia: Insights from functional gradient analyses.

Background: Auditory Verbal Hallucinations (AVH) constitute a prominent feature of schizophrenia. Although low-frequency repetitive transcranial magnetic stimulation (rTMS) has demonstrated therapeutic benefits in ameliorating AVH, the underlying mechanisms of its efficacy necessitate further elucidation. Objective: This study investigated the cortical gradient characteristics and their associations with clinical responses in schizophrenia patients with AVH, mediated through 1 Hz rTMS targeting the left temporoparietal junction. Method: Functional gradient metrics were employed to examine the hierarchy patterns of cortical organization, capturing whole-brain functional connectivity profiles in patients and controls. Results: The 1 Hz rTMS treatment effectively ameliorated the positive symptoms in patients, specifically targeting AVH. Initial evaluations revealed expanded global gradient distribution patterns and specific principal gradient variations in certain brain regions in patients at baseline compared to a control cohort. Following treatment, these divergent global and local patterns showed signs of normalizing. Furthermore, there was observed a closer alignment in between-network dispersion among various networks after treatment, including the somatomotor, attention, and limbic networks, indicating a potential harmonization of brain functionality. Conclusion: Low-frequency rTMS induces alternations in principal functional gradient patterns, may serve as imaging markers to elucidate the mechanisms underpinning the therapeutic efficacy of rTMS on AVH in schizophrenia.

Mendelian Randomization Reveals: Triglycerides and Sensorineural Hearing Loss.

BACKGROUND: Sensorineural hearing loss (SNHL) is a multifactorial disorder with potential links to various physiological systems, including the cardiovascular system via blood lipid levels such as triglycerides (TG). This study investigates the causal relationship between TG levels and SNHL using Mendelian randomization (MR), which offers a method to reduce confounding and reverse causality by using genetic variants as instrumental variables. METHODS: Utilizing publicly available genome-wide association study (GWAS) data, we performed a two-sample MR analysis. The initial analysis unveiled a causal relationship between TG (GWAS ID: ebi-a-GCST90018975) and SNHL (GWAS ID: finn b-H8_HL_SEN-NAS). Subsequent analysis validated this through MR with a larger sample size for TG (GWAS ID: ieu-b-111) and SNHL. To conduct the MR analysis, we utilized several methods including inverse-variance weighted (IVW), MR Egger, weighted median, and weighted mode. We also employed Cochrane's Q test to identify any heterogeneity in the MR results. To detect horizontal pleiotropy, we conducted the MR-Egger intercept test and MR pleiotropy residual sum and outliers (MR-PRESSO) test. We performed a leave-one-out analysis to assess the sensitivity of this association. Finally, a meta-analysis of the MR results was undertaken. RESULTS: Our study found a significant positive correlation between TG and SNHL, with OR values of 1.14 (95% CI: 1.07-1.23, p < 0.001) in the IVW analysis and 1.09 (95% CI: 1.03-1.16, p < 0.006) in the replicate analysis. We also found no evidence of horizontal pleiotropy or heterogeneity between the genetic variants (p > 0.05), and a leave-one-out test confirmed the stability and robustness of this association. The meta-analysis combining the initial and replicate analyses showed a significant causal effect with OR values of 1.11 (95% CI: 1.06-1.16, p = 0.01). CONCLUSION: These findings indicate TG as a risk factor for SNHL, suggesting potential pathways for prevention and intervention in populations at risk. This conclusion underscores the importance of managing TG levels as a strategy to mitigate the risk of developing SNHL.

Proteome-wide Mendelian randomization identifies therapeutic targets for ankylosing spondylitis.

Background: Ankylosing Spondylitis (AS) is a chronic inflammatory disorder which can lead to considerable pain and disability. Mendelian randomization (MR) has been extensively applied for repurposing licensed drugs and uncovering new therapeutic targets. Our objective is to pinpoint innovative therapeutic protein targets for AS and assess the potential adverse effects of druggable proteins. Methods: We conducted a comprehensive proteome-wide MR study to assess the causal relationships between plasma proteins and the risk of AS. The plasma proteins were sourced from the UK Biobank Pharma Proteomics Project (UKB-PPP) database, encompassing GWAS data for 2,940 plasma proteins. Additionally, GWAS data for AS were extracted from the R9 version of the Finnish database, including 2,860 patients and 270,964 controls. The colocalization analysis was executed to identify shared causal variants between plasma proteins and AS. Finally, we examined the potential adverse effects of druggable proteins for AS therapy by conducting a phenome-wide association study (PheWAS) utilizing the extensive Finnish database in version R9, encompassing 2,272 phenotypes categorized into 46 groups. Results: The findings revealed a positive genetic association between the predicted plasma levels of six proteins and an elevated risk of AS, while two proteins exhibited an inverse association with AS risk (P fdr < 0.05). Among these eight plasma proteins, colocalization analysis identified AIF1, TNF, FKBPL, AGER, ALDH5A1, and ACOT13 as shared variation with AS(PPH3+PPH4>0.8), suggesting that they represent potential direct targets for AS intervention. Further phenotype-wide association studies have shown some potential side effects of these six targets (P fdr < 0.05). Conclusion: Our investigation examined the causal connections between six plasma proteins and AS, providing a comprehensive understanding of potential therapeutic targets.

Within-Session Reliability of fNIRS in Robot-Assisted Upper-Limb Training.

Functional near-infrared spectroscopy (fNIRS) seems opportune for neurofeedback in robot-assisted rehabilitation training due to its noninvasive, less physical restriction, and no electromagnetic disturbance. Previous research has proved the cross-session reliability of fNIRS responses to non-motor tasks (e.g., visual stimuli) and fine-motor tasks (e.g., finger tapping). However, it is still unknown whether fNIRS responses remain reliable 1) in gross-motor tasks, 2) within a training session, and 3) for different training parameters. Hence, this study aimed to investigate the within-session reliability of fNIRS responses to gross-motor tasks for different training parameters. Ten healthy participants were recruited to conduct right elbow extension-flexion in three robot-assisted modes. The Passive mode was fully motor-actuated, while Active1 and Active2 modes involved active engagement with different resistance levels. FNIRS data of three identical runs were used to assess the within-session reliability in terms of the map- ( R2 ) and cluster-wise ( Roverlap ) spatial reproducibility and the intraclass correlation (ICC) of temporal features. The results revealed good spatial reliability ( R2 up to 0.69, Roverlap up to 0.68) at the subject level. Besides, the within-session temporal reliabilities of Slope, Max/Min, and Mean were between good and excellent ( ICC < 0.86). We also found that the within-session reliability was positively correlated with the intensity of the training mode, except for the temporal reliability of HbO in Active2 mode. Overall, our results demonstrated good within-session reliability of fNIRS responses, suggesting fNIRS as reliable neurofeedback for constructing closed-loop robot-assisted rehabilitation systems.

Association of neutrophil-to-lymphocyte ratio and risk of cardiovascular and all-cause mortality in hypertension patients.

Background and objective: Hypertension affects over a billion people worldwide and is often associated with poor prognoses. The neutrophil-to-lymphocyte ratio (NLR) has become a significant marker, showing a connection to adverse outcomes in cardiovascular diseases (CVDs). The objective of this study is to examine the relationship between the NLR and outcomes in patients with hypertension. Methods: The study included hypertensive individuals who were surveyed in the National Health and Nutrition Examination Survey (NHANES) from 2009 to 2018. Mortality status was determined using the data from National Death Index (NDI). To investigate the dose-response relationship, restricted cubic spline (RCS) models were used. This study employed adjusted cox proportional hazards regression models to compute hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs) for all-cause and cardiovascular mortality. The predictive accuracy of the NLR for survival outcomes was assessed utilizing time-dependent receiver operating characteristic (ROC) curve analysis. Results: A total of 13,724 participants were included in the final analysis, including 7073 males and 6651 females. The cohort was stratified into higher (>2.0) and lower (≤2.0) NLR groups according to the median value. Over a median follow-up of 64 months, there were 1619 all-cause deaths and 522 cardiovascular deaths among participants. The RCS analysis indicated a non-linear relationship between NLR and the risk of mortality. The adjusted model showed that the group with a higher NLR had a significantly higher risk of all-cause (HR 1.47, 95% CI 1.22-1.77) and cardiovascular mortality (HR 2.08, 95% CI 1.52-2.86). ROC analysis showed that the area under the curves (AUCs) of 0.692, 0.662, 0.644, and 0.625 for predicting all-cause mortality, and 0.712, 0.692, 0.687, and 0.660 for cardiovascular mortality at 1, 3, 5, and 10 years. Conclusion: Elevated NLR is associated with increased risk of cardiovascular and all-cause mortality, and NLR may independently predict outcomes in individuals with hypertension.

Unveiling the flames: macrophage pyroptosis and its crucial role in liver diseases.

Macrophages play a critical role in innate immunity, with approximately 90% of the total macrophage population in the human body residing in the liver. This population encompasses both resident and infiltrating macrophages. Recent studies highlight the pivotal role of liver macrophages in various aspects such as liver inflammation, regeneration, and immune regulation. A novel pro-inflammatory programmed cell death, pyroptosis, initially identified in macrophages, has garnered substantial attention since its discovery. Studies investigating pyroptosis and inflammation progression have particularly centered around macrophages. In liver diseases, pyroptosis plays an important role in driving the inflammatory response, facilitating the fibrotic process, and promoting tumor progression. Notably, the role of macrophage pyroptosis cannot be understated. This review primarily focuses on the role of macrophage pyroptosis in liver diseases. Additionally, it underscores the therapeutic potential inherent in targeting macrophage pyroptosis.

Low-frequency rTMS induces modifications in cortical structural connectivity - functional connectivity coupling in schizophrenia patients with auditory verbal hallucinations.

Auditory verbal hallucinations (AVH) are distinctive clinical manifestations of schizophrenia. While low-frequency repetitive transcranial magnetic stimulation (rTMS) has demonstrated potential in mitigating AVH, the precise mechanisms by which it operates remain obscure. This study aimed to investigate alternations in structural connectivity and functional connectivity (SC-FC) coupling among schizophrenia patients with AVH prior to and following treatment with 1 Hz rTMS that specifically targets the left temporoparietal junction. Initially, patients exhibited significantly reduced macroscopic whole brain level SC-FC coupling compared to healthy controls. Notably, SC-FC coupling increased significantly across multiple networks, including the somatomotor, dorsal attention, ventral attention, frontoparietal control, and default mode networks, following rTMS treatment. Significant alternations in SC-FC coupling were noted in critical nodes comprising the somatomotor network and the default mode network, such as the precentral gyrus and the ventromedial prefrontal cortex, respectively. The alternations in SC-FC coupling exhibited a correlation with the amelioration of clinical symptom. The results of our study illuminate the intricate relationship between white matter structures and neuronal activity in patients who are receiving low-frequency rTMS. This advances our understanding of the foundational mechanisms underlying rTMS treatment for AVH.

Loading Recognition for Lumbar Exoskeleton Based on Multi-Channel Surface Electromyography From Low Back Muscles.

Lumbar exoskeleton is an assistive robot, which can reduce the risk of injury and pain in low back muscles when lifting heavy objects. An important challenge it faces involves enhancing assistance with minimal muscle energy consumption. One of the viable solutions is to adjust the force or torque of assistance in response to changes in the load on the low back muscles. It requires accurate loading recognition, which has yet to yield satisfactory outcomes due to the limitations of available measurement tools and load classification methods. This study aimed to precisely identify muscle loading using a multi-channel surface electromyographic (sEMG) electrode array on the low back muscles, combined with a participant-specific load classification method. Ten healthy participants performed a stoop lifting task with objects of varying weights, while sEMG data was collected from the low back muscles using a 3x7 electrode array. Nineteen time segments of the lifting phase were identified, and time-domain sEMG features were extracted from each segment. Participant-specific classifiers were built using four classification algorithms to determine the object weight in each time segment, and the classification performance was evaluated using a 5-fold cross-validation method. The artificial neural network classifier achieved an impressive accuracy of up to 96%, consistently improving as the lifting phase progressed, peaking towards the end of the lifting movement. This study successfully achieves accurate recognition of load on low back muscles during the object lifting task. The obtained results hold significant potential in effectively reducing muscle energy consumption when wearing a lumbar exoskeleton.

An interpretable model based on graph learning for diagnosis of Parkinson's disease with voice-related EEG.

Parkinson's disease (PD) exhibits significant clinical heterogeneity, presenting challenges in the identification of reliable electroencephalogram (EEG) biomarkers. Machine learning techniques have been integrated with resting-state EEG for PD diagnosis, but their practicality is constrained by the interpretable features and the stochastic nature of resting-state EEG. The present study proposes a novel and interpretable deep learning model, graph signal processing-graph convolutional networks (GSP-GCNs), using event-related EEG data obtained from a specific task involving vocal pitch regulation for PD diagnosis. By incorporating both local and global information from single-hop and multi-hop networks, our proposed GSP-GCNs models achieved an averaged classification accuracy of 90.2%, exhibiting a significant improvement of 9.5% over other deep learning models. Moreover, the interpretability analysis revealed discriminative distributions of large-scale EEG networks and topographic map of microstate MS5 learned by our models, primarily located in the left ventral premotor cortex, superior temporal gyrus, and Broca's area that are implicated in PD-related speech disorders, reflecting our GSP-GCN models' ability to provide interpretable insights identifying distinctive EEG biomarkers from large-scale networks. These findings demonstrate the potential of interpretable deep learning models coupled with voice-related EEG signals for distinguishing PD patients from healthy controls with accuracy and elucidating the underlying neurobiological mechanisms.