Search Results (209)

Introduction: Fish skin is the first line of defense against the aquatic environment, acting as a physical, chemical, and immunological barrier. In addition to preventing pathogen entry, the skin and its mucus contribute to osmoregulation, innate immunity, and redox balance. Skin lesions—caused by mechanical damage, parasites, environmental stress, or handling—disrupt this barrier, increasing susceptibility to infections, inflammation, and production losses. Thus, efficient skin regeneration is essential for fish welfare and performance. Nutrition plays a key role in this process by providing substrates for epithelial repair, immune function, and antioxidant defense. Among dietary factors, zinc (Zn) is particularly important due to its involvement in cell proliferation, enzymatic activity, and maintenance of skin integrity. Objective: Our objective is to assess the effectiveness of image-based analysis in quantifying the skin healing process in Atlantic salmon fed diets supplemented with zinc. Methodology: The trial comprised three dietary treatments: a control diet with 42 mg Zn per kg (D1), and two diets supplemented up to 120 mg/kg of zinc, derived from inorganic (D2) or organic (D3) forms. Pit-tagged fish with an initial body weight (78 ± 0.1 g) were fed the diets for 75 days. After 15 days of experimental feeding, a standardized wound lesion (2.5 mm diameter × 0.5 mm depth) was inflicted in deeply anesthetized fish, with a disposable biopsy punch, in the dorsal area. After wound infliction, the fish resumed their normal feeding regime for the rest of the trial days. The progression of skin wound healing was assessed using standardized digital image analysis. High-resolution photographs of individual wounds were collected 8, 16, 24 and 32 days post-wounding. All images were acquired under standardized conditions with the inclusion of ArUco identifiers to enable a subsequent computer-assisted comparison. Morphometric parameters (wound width, diameter, perimeter and area) were used to assess wound contraction and closure over time. In parallel, a semi-quantitative visual scoring system was applied to each wound image to capture qualitative aspects of healing that are not fully described by morphometric data alone. Results: Full data analysis is currently underway, but the first results show beneficial effects of dietary zinc supplementation on the skin regenerative process. Conclusions: The combined use of objective digital measurements and standardized visual scoring enabled a comprehensive evaluation of wound healing progress, bridging quantitative tissue remodeling with biologically relevant phenotypic outcomes. This image-based framework provides a sensitive and reproducible approach for assessing dietary interventions targeting skin regeneration and barrier restoration in Atlantic salmon. Full article

Optical modules serve as the core transmission interfaces for artificial intelligence computing networks and digital communications. In recent years, demand for these modules has experienced explosive growth. During mass production, the requirements for the accuracy of surface defect detection and noise resistance have continued to rise. Existing POL detection models are susceptible to environmental noise interference; effective defect information is easily overwhelmed by noise entropy, and these models exhibit a high false negative rate for low-contrast and minute defects. This paper proposes a traditional image processing detection scheme that incorporates information entropy constraints. All experimental samples were collected from actual industrial mass production lines. The core process includes: noise suppression during the calibration stage using an entropy-weighted Hough transform; Canny edge detection combined with local entropy filtering for contour localization; and defect fusion recognition based on Hu similarity matching and entropy difference verification. Experimental results show that, compared to traditional POL methods, the proposed approach (WOMC) achieves an average improvement of 35.77% in image clarity and approximately a 2.25-fold increase in detection rate under Gaussian and salt-and-pepper noise conditions. According to statistical analysis of the experiments, this method achieved an accuracy of 96.67%, a recall rate of 97.32%, and a false positive rate of 3.31% in defect detection. In addition, the comprehensive performance score of this detection model reached 96.99%. Moreover, it does not require the deployment of deep-learning models, has a low computing power cost, and is suitable for the detection requirements of large-scale mass production. Full article

Fish phenotyping plays an important role in growth evaluation, selective breeding, and precision aquaculture. Conventional phenotypic measurement methods are labor-intensive, time-consuming, and susceptible to observer variability. To improve measurement efficiency and reproducibility, this study proposes an automated fish phenotyping framework based on Transformer-enhanced instance segmentation. Specifically, a Mask2Former decoder was integrated into the Mask R-CNN architecture to improve boundary delineation and segmentation quality. Based on segmentation outputs, phenotypic parameters, including body length, body height, and projected area, were automatically extracted using PCA-assisted orientation estimation and geometric measurement. In addition, a standardized anatomical landmark annotation framework consisting of 12 reference points was introduced to support reproducible phenotypic description and future extensible morphometric analysis. Body weight was further estimated using polynomial regression based on extracted morphological traits. Experiments were conducted using images from three crucian carp varieties under controlled imaging conditions. The proposed framework achieved 92.7% mAP and 89.4% Boundary IoU, improving segmentation performance over the baseline model. Automated measurement yielded average relative errors of 2.16% for body length and 3.85% for body height, while weight prediction achieved an R² of 0.9479 and a mean relative error of 7.31%. These results demonstrate that Transformer-enhanced segmentation can support accurate and efficient automated phenotyping under standardized conditions and provide a foundation for future deployment in more complex aquaculture environments. Full article

Aphasia is a complex neurological syndrome that includes a multitude of signs and symptoms that describe a patient’s inability to use language (understanding and producing spoken and/or written language) after it has already been acquired, which is caused by cerebral lesions situated in the dominant (left) cerebral hemisphere in right-handed people. Aphasia has a prevalence of 25–30% in acute ischemic stroke (especially in arterial infarcts). In patients who suffered cerebral venous and dural sinuses thrombosis (CVST), aphasia has been noticed in almost 20% of cases, its presence being considered a negative predictive factor. We report the case of a 22-year-old right-handed woman with obesity and active smoking (10 cigarettes/day), undergoing treatment with oral contraceptives who presented to the Emergency Department with an intense headache, resistant to usual analgesic treatment, accompanied by language disorders onset within 24 h. The neurological examination was normal, except for language assessment, which revealed the severe impairment of the repetition domain (she was unable to repeat simple words), and difficulty in naming objects with some hesitations and mild comprehension difficulties (especially in complex orders). She underwent neuroimaging examinations at admission. Native Head Computed Tomography revealed spontaneous hyperdensity (parenchymatous hematoma) in the left temporal lobe. Cranial magnetic resonance imaging (MRI) confirmed venous infarction in the left temporal area and a hypointense signal on MRI T2*SW (susceptibility-weighted) in the region of the left lateral sinus and left jugular vein bulb, which confirmed the thrombosis at this level. Associated cortical vein thrombosis was diagnosed on indirect radiological grounds, since hemorrhagic transformation obscured the direct visualization of the adjacent cortical veins. MR venography was not performed at that time, but instead at the 1-month follow-up, MR venography confirmed the chronic, partial thrombosis of the left lateral sinus and left jugular vein bulb. Laboratory data demonstrated an elevated D-dimer and the presence of homozygosity for MTHFR C677T and PAI-1 4G/4G. Anticoagulation in the form of low-molecular-weight heparin was immediately started, followed by chronic treatment with oral anticoagulant (apixaban) and folic acid. The headaches resolved within three days, and her neurological examination was almost normal: the repetition continued being altered for complex phrases. We did not observe any left lateral sinus thrombosis recurrence, or other extra-cerebral embolic events (deep vein thrombosis or pulmonary embolism) during the follow-up year. The immediate anticoagulation since the admission resulted in a favorable outcome. Taking into consideration our interest in monitoring patients with aphasia secondary to CVST, we also analyzed data from the literature regarding the incidence of conduction aphasia and other aphasic syndromes in this CVST. Due to the limited number of articles identified in the last 21 years (2005–2026) in the literature, we concluded that conduction aphasia is an extremely rare clinical presentation in this kind of pathology and further studies should be conducted in order to identify significant statistical data. Full article

Oil and gas pipelines are crucial component of the strategic infrastructure in China, but they are severely threatened by geological disasters in complex terrains. These disasters may cause pipeline rupture, leakage or explosion, resulting in significant economic losses, environmental pollution and casualties. Traditional manual disaster investigation is inefficient because the pipelines are widely distributed, access is limited and the terrain may be rugged. Therefore, efficient and accurate disaster identification and risk assessment have become a priority that the industry urgently needs to address. Taking the Jiangxi section of the West Line II Zhangshu–Xiangtan connection line as the research area, this study combines the SBAS-InSAR technology with spatial analysis based on GIS to support early disaster identification, surface deformation monitoring and vulnerability assessment. The analysis of 48 Sentinel-1A satellite images shows that the regional ground deformation range is −19.5 to 19.1 mm per year, and most areas show a slow deformation of within ±10 mm per year. The preliminary visual interpretation of the SBAS-InSAR ground deformation data yields 121 preliminary high-deformation disaster points. Combined with the 9 key assessment factors in the GIS platform and the entropy-weighted information model obtained from the geological disaster susceptibility evaluation map and using the optical remote sensing images, 21 human interference points are excluded, and finally 100 potential geological disaster hazard areas are retained. Field verification was conducted through ground reconnaissance surveys and confirmed that 78 of these areas have geological disaster hazards such as landslide, collapses, and slope water damage, providing solid technical support for geological disaster management, monitoring and early warning along the pipeline route. This study proposes a multi-source integrated framework combining SBAS-InSAR, GIS-based susceptibility assessment, and optical validation for improving the reliability of early geological hazard identification. Full article

Background/Objectives: Intramedullary tumors are uncommon spinal cord lesions that account for a small proportion of central nervous system neoplasms but are associated with a high risk of neurological morbidity. Accurate preoperative characterization is essential because therapeutic strategies, surgical planning, and functional prognosis depend strongly on tumor biology and growth behavior within the confined spinal cord environment. This study aims to characterize the radiological phenotype of intramedullary tumors and to identify imaging patterns that may assist in lesion characterization and diagnostic stratification. Methods: A retrospective analysis of preoperative MRI findings in patients with histopathologically confirmed intramedullary tumors was performed. Preoperative MRI examinations were systematically analyzed to describe imaging features according to tumor histology using conventional sequences (T1-weighted, T2-weighted, and contrast-enhanced imaging). Results: Distinct radiological phenotypes were observed across a wide spectrum of lesions. Glial tumors, including subependymoma, ependymoma, pilocytic astrocytoma, diffuse midline glioma H3K27M, glioblastoma, high-grade astrocytoma with piloid features, ganglioglioma, and diffuse leptomeningeal glioneural tumors, demonstrated variable combinations of cord expansion, margin definition, enhancement patterns, and tract involvement, reflecting differences between expansile and infiltrative growth. Secondary tumors such as metastases frequently exhibited aggressive imaging features, including extensive edema and intense or heterogeneous enhancement. Vascular lesions, including hemangioblastoma and cavernoma, showed characteristic vascular signatures, such as nodular enhancement with flow voids or susceptibility-related signal changes. Developmental lesions, such as epidermoid cysts, neurenteric cysts, and lipoma, displayed distinctive signal characteristics, especially on diffusion and T1, that aided differentiation from neoplastic processes. Conclusions: In conclusion, the structured radiological interpretation functions proposed herein are not only useful for diagnostic purposes, but could also be useful for risk stratification and therapeutic guidance. Full article

Background/Objectives: Multiple sclerosis (MS) remains challenging to diagnose due to clinical and radiological overlap with mimicking conditions. The 2024 revisions of the McDonald criteria have incorporated the central vein sign (CVS) and paramagnetic rim lesions (PRLs) as magnetic resonance imaging (MRI) biomarkers to improve diagnostic specificity. This study assessed the prevalence and anatomical distribution of CVS and PRLs in patients with relapsing–remitting MS (RRMS). Methods: This cross-sectional study included 91 patients with RRMS diagnosed according to the 2017 McDonald criteria. MRI scans were obtained using 3T scanners, and T2-FLAIR and susceptibility-weighted angiography (SWAN) sequences were analyzed. CVS and PRLs were identified using established criteria. Patients were stratified by lesion count (<5, 5–9, ≥10), and lesions were categorized by anatomical location. Descriptive statistics, chi-square tests, and multivariable logistic regression adjusted for covariates were performed. Results: CVS was present in 69.2% of patients, while PRLs were identified in 29.7%. Both markers were more frequent in patients with higher lesion burden in univariate analysis. CVS prevalence increased significantly with lesion count (p < 0.001) and remained an independent predictor in multivariable logistic regression. PRL presence was associated with lesion count in univariate analysis but not after adjustment. Most CVS- and PRL-positive lesions were supratentorial and predominantly periventricular. No significant association was observed between CVS and PRL presence. Conclusions: CVS is a highly prevalent MRI feature in RRMS and independently associated with lesion burden, supporting its role as a diagnostically relevant imaging marker. PRLs were less prevalent and showed weaker independent associations. Full article

Background: Ulcerative colitis (UC) is a chronic relapsing inflammatory bowel disease. Intestinal barrier impairment represents a core pathogenic mechanism and a key therapeutic target for achieving mucosal healing and sustained remission. Methods: This narrative review summarizes intestinal barrier structure, disruption mechanisms, barrier-targeted therapies, and non-invasive monitoring approaches. A reproducible literature search was conducted in PubMed, Web of Science, and ClinicalTrials.gov from 2015 to 2026. Results: Barrier disruption in UC involves genetic susceptibility, proinflammatory cytokines, zonulin-mediated tight junction injury, gut microbiota dysbiosis, decreased short-chain fatty acids and secondary bile acids, impaired autophagy, and an abnormal mucin 2 (MUC2)-dependent mucus layer. Validated non-invasive monitoring tools include fecal calprotectin/lactoferrin, intestinal ultrasound, diffusion-weighted magnetic resonance imaging (MRI), and intravoxel incoherent motion (IVIM). Emerging therapies focus on tight junction stabilization, epithelial regeneration, autophagy regulation, MUC2 restoration, and microbiota modulation. Conclusions: Intestinal barrier dysfunction drives the initiation and progression of UC. Barrier-based monitoring and targeted repair strategies improve UC management. Future studies should develop personalized therapies, precise microbiota engineering, and multi-dimensional digital evaluation systems. Full article

Background: Cerebral arteriovenous malformations (AVMs) are high-flow shunts in which abnormal arteriovenous connections expose draining veins to venous hypertension, arterialization, and altered oxygenation. While digital subtraction angiography (DSA) remains the reference standard for dynamic angioarchitecture, it does not directly characterize venous oxygenation or microhemorrhagic tissue changes. Objective: To synthesize current evidence on susceptibility-based MRI-susceptibility-weighted imaging (SWI) and quantitative susceptibility mapping (QSM) for characterization, risk-related features, and treatment monitoring in cerebral AVMs. Methods: Narrative review of the foundational and contemporary literature on AVM pathophysiology, SWI and QSM technical principles, and clinical applications including venous drainage depiction, microhemorrhage detection, oxygenation-related biomarkers, and post-treatment surveillance. Results: SWI provides high-resolution, non-contrast depiction of venous drainage and perinidal hemorrhagic/calcific components, improving visualization of draining veins and microhemorrhages compared with conventional MRI and complementing TOF-MRA. Arterialized draining veins may show altered SWI signal consistent with elevated venous oxygen saturation, though interpretation is indirect and influenced by flow and orientation. QSM extends susceptibility imaging by quantifying tissue susceptibility and enabling indirect estimation of venous oxygenation (SvO₂), offering a potential physiological biomarker of shunt severity and treatment response after radiosurgery or embolization. Key limitations include lack of dynamic flow timing, flow-related artifacts, orientation dependence, confounding from hemorrhage/calcification, and limited standardization and prospective validation. Conclusions: Susceptibility-based MRI does not replace DSA but meaningfully enriches multimodal AVM assessment by adding structural and physiological information-particularly venous mapping, microhemorrhage detection, and oxygenation-sensitive biomarkers. Standardized acquisition/reconstruction and prospective studies are needed to validate susceptibility-derived metrics for risk stratification and longitudinal monitoring. Full article

Background/Objectives: Contrast enhancement (CE) on T1-weighted MRI is routinely used to guide therapy in the management of glioblastoma, although adjacent non-contrast-enhancing (non-CE) T2/FLAIR abnormalities can also harbor viable tumor tissue. The differences between these radiographic compartments remain incompletely characterized beyond conventional structural imaging. We therefore compared CE and non-CE compartments in untreated IDH-wildtype glioblastoma using dynamic susceptibility contrast (DSC) and diffusion-weighted MRI derived indices. Methods: Adults with untreated glioblastoma imaged preoperatively between January 2021 and September 2024 on multi-vendor 1.5 T and 3 T scanners were retrospectively included. Regions of interest were placed in CE tumor, adjacent non-CE T2/FLAIR hyperintense tissue, and contralateral normal-appearing white matter (NAWM). Mean apparent diffusion coefficient (rADC), cerebral blood volume (rCBV), capillary transit time heterogeneity (rCTH), oxygen extraction fraction (rOEF), and a cerebral metabolic rate of oxygen index (rCMRO₂) were extracted and harmonized for scanner effects and normalized to NAWM. Paired CE–non-CE differences were tested using Wilcoxon signed-rank tests and summarized by Hodges–Lehmann differences with bootstrap 95% confidence intervals. Spearman correlations were used to assess coupling within contrast-enhancing tumor regions. Results: Seventy-two participants were analyzed (median age 67 years; 34 women); 66 had paired CE and non-CE data. rCMRO₂ and rCBV were higher in CE than non-CE (both p < 0.001), while rADC was lower (p = 0.003). rOEF (p = 0.12) and rCTH (p = 0.52) did not differ significantly between compartments. Conclusions: CE in untreated IDH-wildtype glioblastoma predominantly reflects higher perfusion capacity (rCBV) along with a higher model-derived rCMRO₂ index, while capillary-function indices (rCTH and rOEF) are not consistently compartment-restricted. These findings may refine the physiological interpretation of CE in glioblastoma and support further validation of DSC-derived indices. Full article

In disease control and precision management in aquaculture, rapid and accurate identification of common fish diseases is pivotal to mitigating economic losses and ensuring aquaculture profitability. However, fish diseases are characterized by subtle symptoms, polymorphic lesions, and high susceptibility to environmental perturbations such as water turbidity and illumination fluctuations. Existing detection models generally suffer from inadequate lightweight design, poor fine-grained lesion feature extraction, and deficient adaptability to class imbalance, failing to meet the stringent requirements of precise diagnosis in real-world aquaculture scenarios. To address these challenges, this study proposes FDR-Net: a fine-grained lesion detection model for tilapia via multi-scale feature enhancement and spatial attention fusion. Using image data of Nile tilapia (Oreochromis niloticus) covering 6 common diseases and healthy individuals (from the NTD-1 dataset), the model incorporates symmetry-aware design logic, leveraging the morphological and textural symmetry of healthy tilapia tissues to capture lesion-induced symmetry-breaking features, thereby improving fine-grained lesion detection accuracy. Through depth-width scaling coefficients, FDR-Net achieves lightweight optimization while integrating three core modules and a task-specific loss function for full-chain optimization: specifically, a Micro-lesion Feature Enhancement Module (MLFEM) is embedded in key feature layers of the backbone network to accurately extract edge and texture features of incipient fine-grained lesions via multi-scale frequency decomposition and residual fusion; subsequently, a Lightweight Multi-scale Position Attention Module (MS_PSA) and a Single-modal Intra-feature Contrastive Fusion Module (SMICFM) are collaboratively deployed—the former focusing on spatial localization of lesion features, and the latter enhancing lesion-background discriminability through channel-spatial feature recalibration and contrastive fusion; finally, a Class-Aware Weighted Hybrid Loss (CAWHL) function is combined with customized small-target anchor boxes to alleviate class imbalance and further improve localization and classification accuracy of fine-grained lesions. Empirical evaluations on the NTD-1 dataset demonstrate that compared with mainstream state-of-the-art baseline models, FDR-Net achieves a peak recognition accuracy of 90.1% with substantially enhanced mAP_50-95 performance. Retaining lightweight characteristics, it exhibits superior performance in identifying incipient fine-grained lesions and strong adaptability to simulated complex aquaculture scenarios. Collectively, this study provides an efficient technical backbone for the rapid and precise detection of tilapia fine-grained lesions, offering a potential solution for precise disease management in tilapia farming. Full article

Background/Objectives: Prosthetic valve endocarditis caused by non-tuberculous mycobacteria is a rare but serious condition and is often associated with delayed diagnosis due to initially negative routine blood cultures with late positivity after prolonged incubation. Mycobacterium fortuitum, a rapidly growing mycobacterium, is an uncommon cause of endocarditis but may result in significant morbidity if not promptly identified. Methods: We report a 67-year-old man with prior cardiac surgery who presented 18 months later with recurrent fever, weight loss, and renal dysfunction. Initial blood cultures, echocardiography, and standard imaging were non-diagnostic. Ongoing clinical suspicion prompted extended mycobacterial cultures with prolonged incubation and molecular identification performed at a reference laboratory, which revealed M. fortuitum. Results: Antimicrobial susceptibility testing demonstrated susceptibility to amikacin, ciprofloxacin, and clarithromycin, and treatment was initiated with an amikacin-based combination regimen. The patient showed marked clinical and laboratory improvement, including resolution of fever and stabilization of renal function. Conclusions: This case highlights the diagnostic and therapeutic challenges of M. fortuitum prosthetic valve endocarditis and underscores the limitations of routine diagnostic methods in culture-negative endocarditis. It also emphasizes the importance of prolonged incubation and targeted microbiological workflows in suspected cases. Full article

Background and Objective: Axial spondyloarthritis (axSpA) is a group of chronic inflammatory diseases that primarily affect the sacroiliac joints. Early diagnosis is crucial for preventing irreversible structural damage. Magnetic Resonance Imaging (MRI) is the gold standard for detecting early inflammatory changes such as sacroiliitis. However, conventional MRI interpretation is inherently subjective and susceptible to both intra- and inter-observer variability. Therefore, artificial intelligence (AI)-driven diagnostic solutions are increasingly being explored. Among them, the Gated Attention Multiple Instance Learning (MIL) framework holds strong potential in modeling heterogeneous inflammatory distributions, thanks to its slice-level attention mechanism. This study aims to evaluate the diagnostic performance of a deep learning model based on Gated Attention MIL for automated sacroiliitis detection. Furthermore, its results are compared with a baseline deep learning architecture (standard ResNet-18), and its consistency with radiologist annotations is analyzed. Materials and Methods: The dataset included 554 subjects, comprising 276 patients diagnosed with axSpA and 278 healthy controls. All MRI data were derived from axial T2-weighted fat-suppressed (T2_TSE_TRA_FS) sequences. Patient-wise data splitting was employed to construct training, validation, and independent test sets. The proposed model architecture integrates ResNet-18-based feature extraction, a gated attention mechanism for instance-level weighting, and bag-level classification. Additionally, Test-Time Augmentation (TTA) was implemented to enhance robustness during inference. Results: On the independent test set, the model achieved an accuracy of 85.88%, sensitivity of 92.86%, specificity of 79.07%, and an F1-score of 86.67%. Attention heatmaps generated by the MIL module showed strong spatial overlap with bone marrow edema regions annotated by expert radiologists. Implementation of TTA led to an approximate 10% improvement in overall classification accuracy. Conclusions: The Gated Attention MIL framework demonstrated high diagnostic performance for sacroiliitis detection, indicating its value as a reliable decision support tool for early axSpA diagnosis. Validation on larger, multi-center datasets is warranted to ensure generalizability and to support clinical integration in routine radiology workflows. Full article

Background/Objectives: Acute ischemic stroke (AIS) is one of the leading causes of mortality worldwide and the primary cause of acquired neurological disability in adults. As part of a stroke magnetic resonance (MR) protocol, fluid-attenuated inversion recovery (FLAIR) plays an important role in the detection and assessment of the degree of leukoaraiosis (LA), while susceptibility-weighted angiography (SWAN) detects cerebral microbleeds (CMBs). The present study sought to examine the association of the degree of LA and CMBs with absolute cerebral blood flow (aCBF) values and functional outcome prediction in patients with AIS. Methods: We conducted a cross-sectional study including a total of 205 male and female patients. All of the patients underwent brain magnetic resonance imaging (MRI) examinations in the first 24 h following suspected AIS, using the stroke protocol. A modified Rankin scale (mRS) was used to evaluate the degree of functional dependence and disability three months after AIS. Results: The incidence of an unfavorable functional outcome evidently increased with more pronounced LA modalities (p < 0.05; χ² test). The Kruskal–Wallis test found a statistically significant difference in aCBF values in relation to a degree of LA (p < 0.05). As there were a small number of multiple CMBs, no statistically significant difference was found based on the detection and degree of CMBs with aCBF and functional outcome; hence, the hypothesis was not entirely confirmed. Conclusions: This study indicates the reliability of MRI application in the initial diagnostic evaluation in order to gain an additional insight into the prediction of AIS outcomes. We demonstrated that LA correlates significantly with an unfavorable functional outcome after AIS, with decreased perfusion values. On the other hand, a higher proportion of unfavorable functional outcomes was observed in patients with CMBs. However, this result was not statistically significant and should be interpreted with caution. Full article

A 79-year-old former marathoner, with memory impairment since age 78, developed increasing stumbling and progressively worsening waddling gait. Three months after gait disturbance onset, she noted mild dysphagia. With declining walking distance and endurance, she presented to our hospital six months after onset, exhibiting frontal signs, Parkinsonism with marked trunk rigidity, and hyperreflexia of the jaw and limbs. L-dopa challenge tests showed no improvement. At seven months post-onset, she had difficulty rising. By nine months, she relied on a walker, and speech disturbance appeared. At 10–11 months, both dysarthria and dysphagia rapidly worsened, she became bed-ridden, and upper limb weakness developed (though she could still use chopsticks). Neurological examination at one year revealed severe dysarthria/dysphagia, four extremity fasciculations and muscle weakness (grade 2 in upper limbs, grade 1 in lower limbs), trunk-dominant rigidity, and hyperreflexia in the jaw and limbs. Brain MRI, specifically susceptibility-weighted imaging, revealed motor band signs. Cerebrospinal fluid study revealed albuminocytological dissociation. Needle electromyography revealed acute denervation and chronic reinnervation in the cranial nerve, cervical, and lumbar areas, which was suggestive of motor neuron disease (MND). Serum anti-GQ1b antibodies were detected. Immunotherapy was followed by mild improvement, which might suggest a reversible component, although definitive pathological overlap remains unconfirmed. This case highlights a diagnostic challenge where an acute immune-mediated neuropathy could potentially be superimposed on a chronic neurodegenerative process. Anti-GQ1b antibodies should be interpreted with caution, as they may reflect either a true clinicopathological overlap with Guillain-Barré syndrome or a secondary phenomenon (epiphenomenon) related to the primary neurodegenerative process. Full article