Explore the vast range of titles available.

Background: The objective of this study was to evaluate the efficacy and safety of repeated low-dose rituximab treatment guided by monitoring circulating CD19+ B cells in patients with refractory myasthenia gravis (MG). Methods: Patients with refractory MG who had received rituximab treatment at two teaching hospitals between September 2013 and January 2017 were reviewed retrospectively. The treatment protocol consisted of an induction treatment with low-dose rituximab (375 mg/m2 twice with a 2-week interval), followed by retreatment (375 mg/m2 once). Retreatment was based on either circulating CD19+ B-cell repopulation or clinical relapse. Outcome measures included the MG Foundation of America (MGFA) clinical classification and postintervention status, prednisolone dose, CD19+ B-cell counts, clinical relapse, and adverse effects. Results: Of 17 patients, 11 (65%) achieved the primary endpoint, defined as the minimal manifestation or better status with prednisolone ⩽5 mg/day, after median 7.6 months (range, 2–17 months) following rituximab treatment. Over a median follow up of 24 months (range, 7–49 months), a total of 30 retreatments were undertaken due to clinical relapse without B-cell repopulation (n = 6), on the basis of B-cell repopulation alone (n = 16) and both (n = 8). B-cell recovery appeared to be in parallel with clinical relapse on the group level, although the individual-level association appeared to be modest, with B-cell repopulation observed only at 57% (8/14) of clinical relapses. Conclusions: The repeated low-dose rituximab treatment based on the assessment of circulating B-cell depletion could be a cost-effective therapeutic option for refractory MG. Further studies are needed to verify the potentially better cost-effectiveness of low-dose rituximab, and to identify biomarkers that help optimize treatment in MG patients.

The split-hand phenomenon is an early and specific feature of amyotrophic lateral sclerosis (ALS). This study aimed to investigate whether the split-hand phenomenon in ALS is associated with the white matter degeneration of the brain. Patients diagnosed with clinically definite or probable ALS were prospectively recruited and underwent both nerve conduction studies to assess the split-hand index (SHI) and brain diffusion tensor imaging (DTI). Demographic, clinical, and electrophysiological data were all collected. A total of 35 patients with ALS (18 male; median age, 66.0 years) were enrolled in this study. The axial diffusivity (AD) and mode of anisotropy (MO) values of DTI in the corticospinal tract (CST) positively correlated with the SHI. However, there were no significant correlations between the SHI and the fraction anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) scalars. In addition, patients having ALS with bilateral split-hand phenomenon showed reduced AD values in the left CST and reduced MO values in the bilateral CST compared with those without the split-hand phenomenon. However, there were no significant differences in FA, MD, and RD scalars. Our findings suggest that the split-hand phenomenon is associated with degenerative brain changes, particularly in the CST.

The measurement of skeletal muscle mass is essential for the diagnosis of sarcopenia. Muscle ultrasonography has emerged as a useful tool for evaluating sarcopenia because it can be used to assess muscle quality and quantity. This study investigated whether muscle ultrasonography is effective for estimating appendicular skeletal muscle mass (ASM) and screening for sarcopenia. This study prospectively enrolled 212 healthy volunteers aged 40–80 years. ASM was measured using the bioelectrical impedance analysis. Muscle thickness (MT) and echo-intensity (EI) were measured in four muscles (biceps brachii, BB; triceps brachii, TB; rectus femoris, RF; biceps femoris, BF) on the dominant hand. A hold-out cross-validation method was used to develop and validate the ASM prediction equation. In the model development group, the ASM prediction equations were deduced as follows: estimated ASM for men (kg) = 0.167 × weight (kg) + 0.228 × height (cm) + 0.143 × MT of BF (mm)– 0.822 × EI to MT ratio of BB– 28.187 (R 2 = 0.830) and estimated ASM for women (kg) = 0.115 × weight + 0.215 × height (cm) + 0.139 × MT of RF–0.638 × EI to MT ratio of BB– 23.502 (R 2 = 0.859). In the cross-validation group, the estimated ASM did not significantly differ from the measured ASM in both men (p = 0.775; intraclass correlation coefficient [ICC] = 0.948) and women (p = 0.516; ICC = 0.973). In addition, multiple logistic regression analysis revealed that the ratios of EI to MT in the BF and RF muscles in men and MT in the BB muscle in women could be valuable parameters for sarcopenia screening. Therefore, our study suggests that muscle ultrasound could be an effective tool for estimating ASM and screening sarcopenia.

The need for developing a simple and effective assessment tool for muscle mass has been increasing in a rapidly aging society. This study aimed to evaluate the feasibility of the surface electromyography (sEMG) parameters for estimating muscle mass. Overall, 212 healthy volunteers participated in this study. Maximal voluntary contraction (MVC) strength and root mean square (RMS) values of motor unit potentials from surface electrodes on each muscle (biceps brachii, triceps brachii, biceps femoris, rectus femoris) during isometric exercises of elbow flexion (EF), elbow extension (EE), knee flexion (KF), knee extension (KE) were acquired. New variables (MeanRMS, MaxRMS, and RatioRMS) were calculated from RMS values according to each exercise. Bioimpedance analysis (BIA) was performed to determine the segmental lean mass (SLM), segmental fat mass (SFM), and appendicular skeletal muscle mass (ASM). Muscle thicknesses were measured using ultrasonography (US). sEMG parameters showed positive correlations with MVC strength, SLM, ASM, and muscle thickness measured by US, but showed negative correlations with SFM. An equation was developed for ASM: ASM = −26.04 + 20.345 × Height + 0.178 × weight − 2.065 × (1, if female; 0, if male) + 0.327 × RatioRMS(KF) + 0.965 × MeanRMS(EE) (SEE = 1.167, adjusted R2 = 0.934). sEMG parameters in controlled conditions may represent overall muscle strength and muscle mass in healthy individuals.

BackgroundOptic neuritis (ON) prognosis is influenced by various factors including attack severity, underlying aetiologies, treatments and consequences of previous episodes. This study, conducted on a large cohort of first ON episodes, aimed to identify unique prognostic factors for each ON subtype, while excluding any potential influence from pre-existing sequelae.MethodsPatients experiencing their first ON episodes, with complete aquaporin-4 (AQP4) and myelin oligodendrocyte glycoprotein (MOG) antibody testing, and clinical data for applying multiple sclerosis (MS) diagnostic criteria, were enrolled. 427 eyes from 355 patients from 10 hospitals were categorised into four subgroups: neuromyelitis optica with AQP4 IgG (NMOSD-ON), MOG antibody-associated disease (MOGAD-ON), ON in MS (MS-ON) or idiopathic ON (ION). Prognostic factors linked to complete recovery (regaining 20/20 visual acuity (VA)) or moderate recovery (regaining 20/40 VA) were assessed through multivariable Cox regression analysis.ResultsVA at nadir emerged as a robust prognostic factor for both complete and moderate recovery, spanning all ON subtypes. Early intravenous methylprednisolone (IVMP) was associated with enhanced complete recovery in NMOSD-ON and MOGAD-ON, but not in MS-ON or ION. Interestingly, in NMOSD-ON, even a slight IVMP delay in IVMP by >3 days had a significant negative impact, whereas a moderate delay up to 7–9 days was permissible in MOGAD-ON. Female sex predicted poor recovery in MOGAD-ON, while older age hindered moderate recovery in NMOSD-ON and ION.ConclusionThis comprehensive multicentre analysis on first-onset ON unveils subtype-specific prognostic factors. These insights will assist tailored treatment strategies and patient counselling for ON.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease. However, no reliable biomarkers have been identified to represent the clinical status. This study aimed to investigate whether diffusion tensor imaging (DTI) findings are useful imaging biomarkers to indicate the clinical status of ALS patients. Ninety-six probable or definite ALS cases and 47 age- and sex-matched, normal controls were enrolled. Demographic and clinical data were collected at the time of DTI. DTI data were acquired using a 3-Tesla magnetic resonance imaging scanner and analysed by voxel-wise statistical analyses for fractional anisotropy, axial diffusivity, radial diffusivity, mean diffusivity, and mode of anisotropy. Compared with the healthy control group, the ALS group had significant differences in DTI scalars in the diffuse tracts of the brain, which was predominant in the corticospinal tract at the brainstem and cerebellar peduncle area. Furthermore, the DTI values correlated with the ALS functional rating scale-revised (ALSFRS-R) scores and the delta ALSFRS-R score representing the rate of disease progression. The subgroup analysis revealed a more severe and widespread brain degeneration was observed in rapidly progressive ALS. Therefore, our results suggest that DTI findings are useful as imaging biomarkers for evaluating the clinical severity and rate of disease progression in ALS.

Step length is a critical hallmark of health status. However, few studies have investigated the modifiable factors that may affect step length. An exploratory, cross-sectional study was performed to evaluate the surface electromyography (sEMG) and body impedance analysis (BIA) parameters, combined with individual demographic data, to predict the individual step length using the GAITRite® system. Healthy participants aged 40–80 years were prospectively recruited, and three models were built to predict individual step length. The first model was the best-fit model (R2 = 0.244, p < 0.001); the root mean square (RMS) values at maximal knee flexion and height were included as significant variables. The second model used all candidate variables, except sEMG variables, and revealed that age, height, and body fat mass (BFM) were significant variables for predicting the average step length (R2 = 0.198, p < 0.001). The third model, which was used to predict step length without sEMG and BIA, showed that only age and height remained significant (R2 = 0.158, p < 0.001). This study revealed that the RMS value at maximal strength knee flexion, height, age, and BFM are important predictors for individual step length, and possibly suggesting that strengthening knee flexor function and reducing BFM may help improve step length.

The glymphatic system plays a critical role in clearing interstitial waste from the brain. Dysfunction of this system has been linked to various neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). The diffusion tensor imaging-along the perivascular space (DTI-ALPS) index has emerged as a potential neuroimaging biomarker for evaluating glymphatic function. This study investigates whether glymphatic function differs in individuals with ALS compared to those with Parkinson's disease (PD) and normal controls (NCs), using the DTI-ALPS index. This study included 35 ALS patients, 35 age- and sex-matched PD patients, and 13 NCs. Diffusion tensor imaging (DTI) was conducted, and the DTI-ALPS index was calculated. Clinical assessments included demographic data, disease duration, cognitive status, and functional scales. Group comparisons and correlation analyses were performed to assess the relationship between the DTI-ALPS index and clinical parameters. The ALS group exhibited a significantly lower right-side DTI-ALPS index than the NC group ( = 0.037), while no differences were observed between the ALS and PD groups. The DTI-ALPS index was negatively correlated with age in ALS and PD groups but showed no correlation with clinical measures in the ALS group. Women in the ALS group had a significantly higher DTI-ALPS index than in men. Glymphatic dysfunction may contribute to the pathogenesis of ALS, as evidenced by a reduced DTI-ALPS index compared to NCs. However, its clinical relevance and specificity for ALS remain uncertain. Further studies with larger cohorts are warranted to validate these findings.

The entorhinal cortex (EC) is one of the earliest cortical regions affected in Alzheimer's disease (AD) and serves as a key target for magnetic resonance imaging (MRI) biomarkers. However, conventional segmentation pipelines based on the Desikan-Killiany atlas do not clearly distinguish the EC from the adjacent perirhinal cortex, leading to mixed labels and reduced diagnostic sensitivity. To address these anatomical ambiguities, we developed a refined EC segmentation framework that combines expert-guided anatomical correction with deep learning. FreeSurfer-derived EC labels were manually refined by removing anterior perirhinal extensions and other anatomically inconsistent regions that are functionally distinct from the EC. These expert-corrected labels were then used to train a no-new-Net (nnU-Net) model on Alzheimer's Disease Neuroimaging Initiative 1 (ADNI1) MRI data, enabling anatomically precise and scalable EC delineation across individuals and scanners. The refined EC segmentation preserved anatomically valid boundaries and demonstrated stronger group-level differentiation among cognitively normal, mild cognitive impairment, and AD groups. When incorporated into volumetric and classification analyses, it provided more specific imaging biomarkers of early neurodegeneration and improved discrimination between diagnostic stages. External validation further confirmed reliable generalization across datasets. These findings demonstrate that anatomically precise and expert-informed EC delineation improves the sensitivity of MRI-based biomarkers for early AD diagnosis. The proposed framework offers a practical and reproducible approach for studying subtle cortical changes that precede overt clinical symptoms.