Hasil untuk "Neurosciences. Biological psychiatry. Neuropsychiatry"

Eun Bit Bae, Jang Wook Sohn, Jang Wook Sohn et al.

The negative impact of the coronavirus disease 2019 (COVID-19) pandemic on mental health, including that of movement restrictions that unintentionally contributed to its deterioration, has been widely reported. However, the effects of isolation and related factors remain unclear. To explore the physiological, psychological, and lifestyle factors that affected stress levels in individuals with confirmed COVID-19 undergoing isolation, we used a modified version of a commercially available wearable device for the purpose of real-time monitoring. The study included 60 infection patients affected by infectious diseases (30 with confirmed COVID-19 undergoing isolation at home, and 30 inpatients at our institution with other infectious diseases). Based on the data distribution, we conducted correlation analyses within each group and evaluated the relationship between variables using conservative methods, general linear regression, and linear mixed models. The groups comparison was evaluated using an independent-samples t-test. Stress scores in the study population showed significant associations with psychological and lifestyle factors, but not with psychiatric scale scores. According to the linear model, caffeine consumption affected the root mean square of successive differences (RMSSD) (p = 0.031). In participants with confirmed COVID-19 undergoing isolation at home, alcohol consumption and anxiety levels showed strong correlations with RMSSD (p< 0.005), although this was not evident in linear models. Stress scores were significantly higher in participants with COVID-19, whereas RMSSD deviation from the mean of an age-matched Korean cohort was significantly lower than that in patients with other infectious diseases. This study suggests that while perceived stress may influence parasympathetic function in all patients with infectious diseases, this effect may be particularly pronounced in those with COVID-19 undergoing isolation. These individuals are more likely to experience stress and anxiety, and their parasympathetic function may be compromised (reflected in a reduction of heart rate variability). Our results suggests that lifestyle factors and perceived stress influences parasympathetic function in under stressful conditions associated with confinement, and that these factors should be considered in the management of individuals with COVID-19 in isolation.

Ziheng Zhang, Xinyue Ma, Arpita Chowdhury et al.

This work investigates descriptive captions as an additional source of supervision for biological multimodal foundation models. Images and captions can be viewed as complementary samples from the latent morphospace of a species, each capturing certain biological traits. Incorporating captions during training encourages alignment with this shared latent structure, emphasizing potentially diagnostic characters while suppressing spurious correlations. The main challenge, however, lies in obtaining faithful, instance-specific captions at scale. This requirement has limited the utilization of natural language supervision in organismal biology compared with many other scientific domains. We complement this gap by generating synthetic captions with multimodal large language models (MLLMs), guided by Wikipedia-derived visual information and taxon-tailored format examples. These domain-specific contexts help reduce hallucination and yield accurate, instance-based descriptive captions. Using these captions, we train BioCAP (i.e., BioCLIP with Captions), a biological foundation model that captures rich semantics and achieves strong performance in species classification and text-image retrieval. These results demonstrate the value of descriptive captions beyond labels in bridging biological images with multimodal foundation models.

Adibvafa Fallahpour, Andrew Magnuson, Purav Gupta et al.

Unlocking deep and interpretable biological reasoning from complex genomic data remains a major AI challenge limiting scientific progress. While current DNA foundation models excel at representing sequences, they struggle with multi-step reasoning and lack transparent, biologically meaningful explanations. BioReason addresses this by tightly integrating a DNA foundation model with a large language model (LLM), enabling the LLM to directly interpret and reason over genomic information. Through supervised fine-tuning and reinforcement learning, BioReason learns to produce logical, biologically coherent deductions. It achieves major performance gains, boosting KEGG-based disease pathway prediction accuracy from 86% to 98% and improving variant effect prediction by an average of 15% over strong baselines. BioReason can reason over unseen biological entities and explain its decisions step by step, offering a transformative framework for interpretable, mechanistic AI in biology. All data, code, and checkpoints are available at https://github.com/bowang-lab/BioReason

Shuyue Jiang, Wenjing Ma, Shaojun Yu et al.

Biological age, which may be older or younger than chronological age due to factors such as genetic predisposition, environmental exposures, serves as a meaningful biomarker of aging processes and can inform risk stratification, treatment planning, and survivorship care in cancer patients. We propose EpiCAge, a multimodal framework that integrates epigenetic and phenotypic data to improve biological age prediction. Evaluated on eight internal and four external cancer cohorts, EpiCAge consistently outperforms existing epigenetic and phenotypic age clocks. Our analyses show that EpiCAge identifies biologically relevant markers, and its derived age acceleration is significantly associated with mortality risk. These results highlight EpiCAge as a promising multimodal machine learning tool for biological age assessment in oncology.

Silje Mørup Ormhaug, Tine K. Jensen, Kate Louise Porcheret et al.

Background: Childhood trauma is a public health challenge, and there is currently a service/needs gap. Low-intensive treatments where the task of leading the treatment is partially shifted to a caregiver can help bridge this gap by freeing therapist resources. Stepping Together for Children after Trauma (ST-CT), is a novel parent-led, therapist-assisted treatment with promising results in the U.S. Also, it has shown to be feasible as a first-line intervention in Norwegian municipal services and ST-CT is well accepted by children, caregivers, and therapists.Objective: This study is the first randomized controlled trial of ST-CT by independent researchers. The study consists of three work-packages: WP1: Investigates (a) the effectiveness of ST-CT compared to therapy as usual (TAU) in reducing post-traumatic stress symptoms (PTSS), related mental health symptoms, sleep problems and increasing daily functioning; (b) the cost-effectiveness of ST-CT compared to TAU in terms of quality adjusted life years; (c) future health care utilization. WP2: Looks at change processes in ST-CT, with changes in sleep, post-traumatic cognitions and child–parent relationship as potential mediators of reductions in child PTSS. WP3: Investigates keys to implementation into regular first-line mental health services.Methods: The study has a type 1 hybrid effectiveness-implementation design. Children between 7-12 years of age with symptoms of PTSS and their caregivers are randomized to either ST-CT or TAU and participants are assessed at five time points during the first year. Sleep quality is measured with a non-contact radar 1 week pre- and post-treatment and registry data of use of prescribed medications and mental health service utilization will be collected 3 years post-inclusion. The study aims to include 160 child–parent dyads from 30 municipalities.Conclusion: Results can help gain a better understanding of the effectiveness and change processes of ST-CT and may provide important knowledge for a future dissemination and implementation.Trial registration: ClinicalTrials.gov identifier: NCT05734547.

Emma Fargher, Marcus Keatinge, Oluwaseyi Pearce et al.

Abstract Single nucleotide polymorphisms adjacent to the α-amino-β-carboxymuconate-ε-semialdehyde decarboxylase (ACMSD) gene have been associated with Parkinson’s disease (PD) in genome-wide association studies (GWAS). However, its biological validation as a PD risk gene has been hampered by the lack of available models. Using CRISPR/Cas9, we generated a zebrafish model of acmsd deficiency with marked increase in quinolinic acid. Despite this, acmsd -/- zebrafish were viable, fertile, morphologically normal and demonstrated no abnormalities in spontaneous movement. In contrast to the postulated pro-immune pathomechanism linking ACMSD to PD, microglial cells and expression of the proinflammatory cytokines cxcl8, il-1β, and mmp9 were similar between acmsd -/- and controls. The number of ascending dopaminergic neurons, and their susceptibility to MPP+, was also indistinguishable. An upregulation of kynurenine aminotransferase activity was identified in acmsd -/- zebrafish which may explain the absence of neurodegenerative phenotypes. Our study highlights the importance of biological validation for putative GWAS hits in suitable model systems.

Plück Julia, Nawab Laurence, Kamenetzka Elena et al.

Based on Achenbach's school-age questionnaires, research groups have investigated supplementary scales for stress problems, obsessive-compulsive problems, sluggish cognitive tempo, positive qualities, dysregulation, autism spectrum disorders, and mania in 6–18-year-olds partly only in some of the three perspectives the Achenbach System of Empirically Based Assessment (ASEBA) provides.

Maria El Helou, Matthieu Hein, Beni-Champion Cimpaye et al.

Introduction: This study aimed to explore the clinical and psychosocial characteristics associated with functional non-remission in young adults involuntarily hospitalized for a first episode of psychosis (FEP), focusing on the role of duration of untreated psychosis (DUP) and contextual vulnerabilities. Material and method: We conducted a retrospective monocentric study including 123 patients aged 18–30 who were involuntarily admitted between 2013 and 2023 for a first psychotic episode. Sociodemographic, clinical, and care-related data were extracted from medical records. Functional remission was defined as a Global Assessment of Functioning (GAF) score ≥70 at discharge. Univariate and multivariate logistic regressions were used to identify predictors of functional non-remission. Results: Only 48.8% of patients achieved functional remission at discharge. Social isolation, low socioeconomic status, unemployment, lack of structured activities, and a DUP ≥ 4 weeks were significantly associated with functional non-remission. After multivariate logistic regressions, DUP ≥ 4 weeks remained an independent predictor of functional non-remission. Conclusions: Involuntary admission per se was not a direct predictor of poor outcome. Our findings highlight the critical role of prolonged DUP and psychosocial vulnerability in the trajectory of early psychosis. Early detection strategies, psychosocial support integration, and individualized care planning are essential to improve outcomes among young people experiencing FEP under compulsory admission.

Tanujit Chakraborty, Swarup Chattopadhyay, Suchismita Das et al.

Complex biological networks, encompassing metabolic pathways, gene regulatory systems, and protein-protein interaction networks, often exhibit scale-free structures characterized by heavy-tailed degree distributions. However, empirical studies reveal significant deviations from ideal power law behavior, underscoring the need for more flexible and accurate probabilistic models. In this work, we propose the Compounded Burr (CBurr) distribution, a novel four parameter family derived by compounding the Burr distribution with a discrete mixing process. This model is specifically designed to capture both the body and tail behavior of real-world network degree distributions with applications to biological networks. We rigorously derive its statistical properties, including moments, hazard and risk functions, and tail behavior, and develop an efficient maximum likelihood estimation framework. The CBurr model demonstrates broad applicability to networks with complex connectivity patterns, particularly in biological, social, and technological domains. Extensive experiments on large-scale biological network datasets show that CBurr consistently outperforms classical power-law, log-normal, and other heavy-tailed models across the full degree spectrum. By providing a statistically grounded and interpretable framework, the CBurr model enhances our ability to characterize the structural heterogeneity of biological networks.

Xing Li, Oussama Zenkri, Adrian Pfisterer et al.

Robustness, the ability of a system to maintain performance under significant and unanticipated environmental changes, is a critical property for robotic systems. While biological systems naturally exhibit robustness, there is no comprehensive understanding of how to achieve similar robustness in robotic systems. In this work, we draw inspirations from biological systems and propose a design principle that advocates active interconnections among system components to enhance robustness to environmental variations. We evaluate this design principle in a challenging long-horizon manipulation task: solving lockboxes. Our extensive simulated and real-world experiments demonstrate that we could enhance robustness against environmental changes by establishing active interconnections among system components without substantial changes in individual components. Our findings suggest that a systematic investigation of design principles in system building is necessary. It also advocates for interdisciplinary collaborations to explore and evaluate additional principles of biological robustness to advance the development of intelligent and adaptable robotic systems.

Congqi Liu, Congqi Liu, Congqi Liu et al.

BackgroundMental health challenges are encountered by frail older adults as the population ages. The extant literature is scant regarding the correlation between depressive symptoms and social participation among frail older adults.MethodsThis study is based on an analysis of data from China Health and Retirement Longitudinal Study (CHARLS) participants aged 60 and older who are frail. A frailty index (FI) was developed for the purpose of assessing the frailty level of the participants. Additionally, latent class analysis (LCA) was employed to classify the participants’ social engagement patterns in 2015 and 2018. The study used ordered logistic regression to examine the relationship between social participation type and depressive symptoms. We also used Latent Transition Analysis (LTA) methods to explore the impact of changes in social activity types on depressive symptoms after three years of follow-up in 2018. In addition, the response surface analysis (RSM) investigation explored the relationship among FI, depression, and social participation.ResultsA total of 4,384 participants completed the baseline survey; three years later, 3,483 were included in the follow-up cohort. The baseline survey indicates that female older adults in rural areas who are single, have lower incomes, shorter sleep durations, and lighter weights exhibited more severe depressive symptoms. Social participation patterns were categorized into five subgroups by LCA. The findings indicate that individuals classified as “board game enthusiasts” (OR, 0.62; 95% CI, 0.47-0.82) and those as “extensive social interaction” (OR,0.67; 95% CI, 0.49-0.90) have a significantly lower likelihood of developing depressive symptoms compared to the “socially isolated” group. We also discovered that “socially isolated” baseline participants who transitioned to the “helpful individual” group after three years had significantly greater depressed symptoms (OR, 1.56; 95% CI, 1.00-2.44). More social activity types and less FI are linked to lower depression in our study.ConclusionThe results of the study emphasize the importance of social participation patterns and the number of social participation types in relation to the severity of depression among frail older adults individuals. This study’s findings may provide important insights for addressing depressive symptoms in frail older adults person.

Alinny R. Isaac, Mariana G. Chauvet, Ricardo Lima-Filho et al.

Abstract Major depressive disorder (MDD) is a significant cause of disability in adults worldwide. However, the underlying causes and mechanisms of MDD are not fully understood, and many patients are refractory to available therapeutic options. Impaired control of brain mRNA translation underlies several neurodevelopmental and neurodegenerative conditions, including autism spectrum disorders and Alzheimer’s disease (AD). Nonetheless, a potential role for mechanisms associated with impaired translational control in depressive-like behavior remains elusive. A key pathway controlling translation initiation relies on the phosphorylation of the α subunit of eukaryotic initiation factor 2 (eIF2α-P) which, in turn, blocks the guanine exchange factor activity of eIF2B, thereby reducing global translation rates. Here we report that the expression of EIF2B5 (which codes for eIF2Bε, the catalytic subunit of eIF2B) is reduced in postmortem MDD prefrontal cortex from two distinct human cohorts and in the frontal cortex of social isolation-induced depressive-like behavior model mice. Further, pharmacological treatment with anisomycin or with salubrinal, an inhibitor of the eIF2α phosphatase GADD34, induces depressive-like behavior in adult C57BL/6J mice. Salubrinal-induced depressive-like behavior is blocked by ISRIB, a compound that directly activates eIF2B regardless of the phosphorylation status of eIF2α, suggesting that increased eIF2α-P promotes depressive-like states. Taken together, our results suggest that impaired eIF2-associated translational control may participate in the pathophysiology of MDD, and underscore eIF2-eIF2B translational axis as a potential target for the development of novel approaches for MDD and related mood disorders.

Rong-Pei Liu, Guo-Liang Lin, Lu-Lu Ma et al.

BackgroundCognitive impairment (CI) is common in Parkinson’s disease (PD). Multiple brain regions and their interactions are involved in PD associated CI. Magnetic resonance imaging (MRI) technology is a non-invasive method in investigating brain structure and inter-regional connections. In this study, by comparing cortical thickness, subcortical volume, and brain network topology properties in PD patients with and without CI, we aimed to understand the changes of brain structure and structural covariance network properties in PD associated CI.MethodsA total of 18 PD patients with CI and 33 PD patients without CI were recruited. Movement Disorder Society Unified Parkinson’s Disease Rating Scale, Hoehn and Yahr stage, Mini Mental State Examination Scale, Non-motor Symptom Rating Scale, Hamilton Anxiety Scale, and Hamilton Depression Scale were assessed. All participants underwent structural 3T MRI. Cortical thickness, subcortical volume, global and nodal network topology properties were measured.ResultsCompared with PD patients without CI, the volumes of white matter, thalamus and hippocampus were lower in PD patients with CI. And decreased whole-brain local efficiency is associated with CI in PD patients. While the cortical thickness and nodal network topology properties were comparable between PD patients with and without CI.ConclusionOur findings support the alterations of brain structure and disruption of structural covariance network are involved in PD associated CI, providing a new insight into the association between graph properties and PD associated CI.

Roy Abel, Shimon Ullman

As part of understanding how the brain learns, ongoing work seeks to combine biological knowledge and current artificial intelligence (AI) modeling in an attempt to find an efficient biologically plausible learning scheme. Current models of biologically plausible learning often use a cortical-like combination of bottom-up (BU) and top-down (TD) processing, where the TD part carries feedback signals used for learning. However, in the visual cortex, the TD pathway plays a second major role of visual attention, by guiding the visual process to locations and tasks of interest. A biological model should therefore combine the two tasks, and learn to guide the visual process. We introduce a model that uses a cortical-like combination of BU and TD processing that naturally integrates the two major functions of the TD stream. The integrated model is obtained by an appropriate connectivity pattern between the BU and TD streams, a novel processing cycle that uses the TD part twice, and the use of 'Counter-Hebb' learning that operates across the streams. We show that the 'Counter-Hebb' mechanism can provide an exact backpropagation synaptic modification. We further demonstrate the model's ability to guide the visual stream to perform a task of interest, achieving competitive performance compared with AI models on standard multi-task learning benchmarks. The successful combination of learning and visual guidance could provide a new view on combining BU and TD processing in human vision, and suggests possible directions for both biologically plausible models and artificial instructed models, such as vision-language models (VLMs).

Alejandra P. Garza, Lorena Morton, Éva Pállinger et al.

Tobacco smoking is strongly linked to vascular damage contributing to the development of hypertension, atherosclerosis, as well as increasing the risk for neurodegeneration. Still, the involvement of the innate immune system in the development of vascular damage upon chronic tobacco use before the onset of clinical symptoms is not fully characterized. Our data provide evidence that a single acute exposure to tobacco elicits the secretion of extracellular vesicles expressing CD105 and CD49e from endothelial cells, granting further recognition of early preclinical biomarkers of vascular damage. Furthermore, we investigated the effects of smoking on the immune system of healthy asymptomatic chronic smokers compared to never-smokers, focusing on the innate immune system. Our data reveal a distinct immune landscape representative for early stages of vascular damage in clinically asymptomatic chronic smokers, before tobacco smoking related diseases develop. These results indicate a dysregulated immuno-vascular axis in chronic tobacco smokers that are otherwise considered as healthy individuals. The distinct alterations are characterized by increased CD36 expression by the blood monocyte subsets, neutrophilia and increased plasma IL-18 and reduced levels of IL-33, IL-10 and IL-8. Additionally, reduced levels of circulating BDNF and elevated sTREM2, which are associated with neurodegeneration, suggest a considerable impact of tobacco smoking on CNS function in clinically healthy individuals. These findings provide profound insight into the initial and ongoing effects of tobacco smoking and the potential vascular damage contributing to neurodegenerative disorders, specifically cerebrovascular dysfunction and dementia.

Fabienne E. Andres, Tracey Thornborrow, Wienis N. Bowie et al.

Abstract Background Body dissatisfaction (BD) is a growing concern in Latin America; reliable and culturally appropriate scales are necessary to support body image research in Spanish speaking Latin American countries. We sought to validate a Latin-American Spanish version of the Body Esteem Scale for Adolescents and Adults (BESAA; Mendelson et al. 2001). Methods The BESAA was translated, culturally adapted, and validated in a sample of adults in Colombia (N = 525, 65% women, M age 24.4, SD = 9.28). We assessed factor structure (using confirmatory factor analysis (CFA), exploratory factor analysis (EFA) and exploratory structural equation model (ESEM)), internal reliability (using Cronbach’s alpha and omega), validity (using the Body Appreciation Scale BAS and Sociocultural Attitudes Towards Appearance Questionnaire SATAQ), test–retest stability in a small subsample (N = 84, using Intraclass correlations ICC) and measurement invariance across gender. To evaluate the generalizability of the scale, we assessed reliability, validity, and factor structure in a second sample from rural Nicaragua (N = 102, 73% women, M age 22.2, SD = 4.72), and assessed measurement invariance across Nicaraguan and Colombian participants. Results The scale showed good internal reliability and validity in both samples, and there was evidence of adequate test–retest stability in the Colombian sample. EFA showed a three-factor structure with subscales we labelled ‘appearance-positive’, ‘appearance-negative’ and ‘weight’, that was confirmed using CFA and ESEM in the Colombian sample. Measurement invariance was confirmed across the Colombian and Nicaraguan samples, and across gender within the Colombian sample. Conclusion The Latin-American Spanish version of the BESAA (BESAA-LA) appears to be a psychometrically sound measure with good reliability, validity and invariance across gender and countries. These results support the use of this scale to measure body satisfaction/dissatisfaction in Latin American adult populations.

Yuhan Helena Liu, Stephen Smith, Stefan Mihalas et al.

The spectacular successes of recurrent neural network models where key parameters are adjusted via backpropagation-based gradient descent have inspired much thought as to how biological neuronal networks might solve the corresponding synaptic credit assignment problem. There is so far little agreement, however, as to how biological networks could implement the necessary backpropagation through time, given widely recognized constraints of biological synaptic network signaling architectures. Here, we propose that extra-synaptic diffusion of local neuromodulators such as neuropeptides may afford an effective mode of backpropagation lying within the bounds of biological plausibility. Going beyond existing temporal truncation-based gradient approximations, our approximate gradient-based update rule, ModProp, propagates credit information through arbitrary time steps. ModProp suggests that modulatory signals can act on receiving cells by convolving their eligibility traces via causal, time-invariant and synapse-type-specific filter taps. Our mathematical analysis of ModProp learning, together with simulation results on benchmark temporal tasks, demonstrate the advantage of ModProp over existing biologically-plausible temporal credit assignment rules. These results suggest a potential neuronal mechanism for signaling credit information related to recurrent interactions over a longer time horizon. Finally, we derive an in-silico implementation of ModProp that could serve as a low-complexity and causal alternative to backpropagation through time.

Shiwei Ng, Benjamin Ng Guan Zhi, Robert E. Simpson et al.

Biological systems evolve with minimum metabolic costs and use common components, and they represent guideposts toward a paradigm of manufacturing that is centered on minimum energy, local resources, and ecological integration. Here, a new method of metalworking that uses chitosan from the arthropod cuticle to aggregate colloidal suspensions of different metals into solid ultra-low-binder-content composites is demonstrated. These composites, which can contain more than 99.5% metal, simultaneously show bonding affinity for biological components and metallic characteristics, such as electrical conductivity. This approach stands in contrast with existing metalworking methods, taking place at ambient temperature and pressure, and being driven by water exchange. Furthermore, all the nonmetallic components involved are metabolized in large amounts in every ecosystem. Under these conditions, the composites' ability to be printed and cast into functional shapes with metallic characteristics is demonstrated. The affinity of chitometallic composites for other biological components also allows them to infuse metallic characteristics into other biomaterials. The findings and robust manufacturing examples go well beyond basic demonstrations and offer a generalizable new approach to metalworking. The potential for a paradigm shift toward biomaterials based on their unique characteristics and the principles of their manufacturing methods is highlighted.

C. Weeland, C. Vriend, Y. Van Der Werf et al.

Introduction Higher thalamic volume has been found in children with obsessive-compulsive disorder (OCD) and children with clinical-level symptoms within the general population (Boedhoe et al. 2017, Weeland et al. 2021a). Functionally distinct thalamic nuclei are an integral part of OCD-relevant brain circuitry. Objectives We aimed to study the thalamic nuclei volume in relation to subclinical and clinical OCD across different age ranges. Understanding the role of thalamic nuclei and their associated circuits in pediatric OCD could lead towards treatment strategies specifically targeting these circuits. Methods We studied the relationship between thalamic nuclei and obsessive-compulsive symptoms (OCS) in a large sample of school-aged children from the Generation R Study (N = 2500) (Weeland et al. 2021b). Using the data from the ENIGMA-OCD working group we conducted mega-analyses to study thalamic subregional volume in OCD across the lifespan in 2,649 OCD patients and 2,774 healthy controls across 29 sites (Weeland et al. 2021c). Thalamic nuclei were grouped into five subregions: anterior, ventral, intralaminar/medial, lateral and pulvinar (Figure 1). Results Both children with subclinical and clinical OCD compared with controls show increased volume across multiple thalamic subregions. Adult OCD patients have decreased volume across all subregions (Figure 2), which was mostly driven by medicated and adult-onset patients. Conclusions Our results suggests that OCD-related thalamic volume differences are global and not driven by particular subregions and that the direction of effects are driven by both age and medication status. Disclosure No significant relationships.

Jung Hwan Park, Chun-Sung Cho

The utilization of carotid artery stenting (CAS) as a less invasive and alternative treatment to carotid endarterectomy (CEA) has progressively increased. However, with the increasing incidence of CAS, several studies have investigated the complication rates of CAS compared to CEA. Recent findings suggest that CAS resulted in better patient prognosis than CEA, following advances in techniques and instrumentation. Despite the decreased procedural risk associated with CAS, one of the most common complications is thromboembolic events. Hyper-perfusion injury and in-stent stenosis due to fibro-proliferation are other complications. However, stent shortening rarely occurs. We present two cases of the downward shortening of a stent after a CAS procedure, which were detected via computed tomography angiography (CTA) the day after stenting, suggesting the possible role of the “watermelon seeding effect.”