Background: Rapid differentiation between ischemic and hemorrhagic stroke is essential because management differs significantly. In settings without immediate neuroimaging, artificial intelligence (AI) may assist early decision-making. To evaluate the performance of AI in distinguishing ischemic from hemorrhagic stroke using history and physical examination alone. Methods: This retrospective, observational, case-control study included 54 adults (27 ischemic, 27 hemorrhagic) with neuroimaging-confirmed stroke in a tertiary hospital from January to June 2025. De-identified clinical data were entered into a structured AI prompt. AI predictions were compared with imaging diagnoses, and accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Results: Ischemic stroke patients were slightly older than hemorrhagic cases; hypertension was the most frequent comorbidity. One-sided weakness was the most common presenting symptom, while headache occurred only in hemorrhagic stroke. Overall accuracy of Google Gemini 2.5 Pro was 66.7% (p = 0.0099). Sensitivity for ischemic stroke was 85.2%, specificity for hemorrhagic stroke was 48.1%, and PPV and NPV were 62.2% and 76.5%, respectively. Conclusion: AI demonstrated moderate diagnostic performance, with greater accuracy for ischemic than hemorrhagic stroke. AI may serve as an adjunct in resource-limited settings but should not replace neuroimaging. Larger studies and model refinement are recommended.
Perineuronal nets (PNNs) are specialized extracellular matrix structures that enwrap select neuronal populations—particularly, parvalbumin-positive inhibitory interneurons. Under physiological conditions, they stabilize synaptic connectivity, regulate excitatory– inhibitory balance, and contribute to the closure of developmental critical periods. Rather than being static scaffolds, PNNs dynamically regulate neuronal excitability, synaptic plasticity, and circuit maturation across the lifespan. Notably, accumulating evidence indicates that the disruption of these functions represents a cross-diagnostic mechanism underlying shared circuit vulnerabilities across multiple brain disorders. In autism spectrum disorder, schizophrenia, bipolar disorder, epilepsy, Alzheimer’s disease, amyotrophic lateral sclerosis, and substance use disorders, alterations in PNN density, composition, and remodeling are consistently associated with disrupted PV interneuron function, impaired network oscillations, and aberrant circuit stability. A central paradox thus emerges: excessive PNN stabilization may prematurely restrict plasticity during development, whereas pathological degradation or dysregulation in adulthood destabilizes mature circuits and increases vulnerability to excitotoxicity, neuroinflammation, and maladaptive memory persistence. These context-dependent effects highlight the translational potential of targeting PNNs to restore circuit balance. Together, these findings position PNNs as critical regulators of the balance between stability and adaptability in neural circuits and underscore their potential as translational targets for circuit-level therapeutic interventions.
Objective To characterize glymphaticu2010 and cerebrospinal fluid (CSF)u2010related imaging alterations in moderateu2010tou2010advanced, deep brain stimulation (DBS)u2010eligible Parkinsonu2019s disease (PD) using a multidimensional magnetic resonance imaging (MRI) framework. Methods We studied 60 moderateu2010tou2010advanced, DBSu2010eligible patients with PD and 30 frequencyu2010matched healthy controls with 3.0 T MRI. The u201CSourceu2010Dynamicsu2010Functionu2010Structureu201D framework integrated choroid plexus volume fraction, C1u2013C2 phaseu2010contrast MRI, diffusion tensor image analysis along the perivascular space index, and perivascular space volumetry. Multivariable analyses were used to examine associations between imaging biomarkers and motor severity, anxiety, and sleep quality. Results Patients with PD showed reduced diffusion tensor image analysis along the perivascular space index, a nominal increase in choroid plexus volume fraction, and a lowu2010netu2010flow CSF pattern with nominal evidence of increased reflux and marked spatial heterogeneity, despite preserved gross perivascular morphology. Ventral CSF dynamics showed significant partial correlations with motor severity, whereas selected dorsal flow metrics remained significantly associated with anxiety severity in covariateu2010adjusted regression analyses. The combined logistic model showed modest diagnostic performance (area under the curve = 0.686), with the highest area under the curve numerically but no statistically significant advantage over individual imaging metrics in paired DeLong comparisons. Conclusion This framework provides an exploratory neuroimaging reference for moderateu2010tou2010advanced, DBSu2010eligible PD and may support future validation studies and DBSu2010related investigations.
Background: Rathke’s cleft cysts (RCCs) are benign sellar and suprasellar lesions. Most are treated conservatively, while others require surgery, usually via a transsphenoidal intervention. However, long-term outcomes of surgical intervention remain challenged by the risk of cyst recurrence, which can manifest years after initial treatment. We aim to assess the long-term outcomes of RCCs and predictors of recurrence post endoscopic endonasal resection. Methods: We reviewed our database for the last 10 years (2014–2024). We included all the patients with Rathke’s Cleft Cysts who underwent Endoscopic Endonasal Transsphenoidal (EET) surgery. Demographic data, preoperative, intraoperative, postoperative clinical data and patients’ outcomes were retrospectively collected and analyzed. Results: Thirty RCC patients who underwent transsphenoidal surgery were included in this study. The mean age of our cohort was 54.6 years, and 59% were females. Four patients developed cerebrospinal fluid (CSF) leak postoperatively (13.33%), and four patients (13.33%) had permanent diabetes insipidus (DI). During follow-up, recurrence was observed in 16.67% (5 patients) with an average latency of 23 months. Only three patients were symptomatic and required re-operation. Conclusions: Following transsphenoidal surgery for Rathke’s cleft cysts, many patients experienced rapid improvement of symptoms. Moreover, recurrence is influenced by numerous factors requiring long-term follow-up. Future studies with larger sample sizes and longer follow-up durations are recommended.
Introduction: Depression is a prevalent psychological problem among higher vocational college students. This study aimed to explore the potential relationships among neurotic personality, maladaptive emotion regulation strategies, anxiety, and depressive symptoms in higher vocational college students. Methods: Higher vocational college students in Jiangxi, China, were recruited for this survey study. The Chinese version of the Eysenck Personality Questionnaire, the Cognitive Emotion Regulation Questionnaire, the Self-assessment Scale of Anxiety, and the Self-depression Scale were administered to assess the mental condition of the students. We used serial mediation models to understand whether maladaptive emotion regulation strategies and anxiety mediate the effect of neurotic personality on depression. Results: Neurotic personality was significantly positively correlated with depression severity (r = 0.52, p < 0.001). Furthermore, catastrophizing (total mediating effect: 1.002) and blame-other strategies (total mediating effect: 0.993), as maladaptive emotion regulation strategies, and anxiety exerted a chain mediating effect on the relationship between neurotic personality and depression. Conclusion: This study revealed the significant effect of neurotic personality on depression in higher vocational college students and its underlying mechanism. Our results may be valuable for maintaining and improving the physical and mental health of higher vocational college students.
Objective: To characterize glymphatic- and cerebrospinal fluid (CSF)-related imaging alterations in moderate-to-advanced, deep brain stimulation (DBS)-eligible Parkinson’s disease (PD) using a multidimensional magnetic resonance imaging (MRI) framework. Methods: We studied 60 moderate-to-advanced, DBS-eligible patients with PD and 30 frequency-matched healthy controls with 3.0 T MRI. The “Source-Dynamics-Function-Structure” framework integrated choroid plexus volume fraction, C1–C2 phase-contrast MRI, diffusion tensor image analysis along the perivascular space index, and perivascular space volumetry. Multivariable analyses were used to examine associations between imaging biomarkers and motor severity, anxiety, and sleep quality. Results: Patients with PD showed reduced diffusion tensor image analysis along the perivascular space index, a nominal increase in choroid plexus volume fraction, and a low-net-flow CSF pattern with nominal evidence of increased reflux and marked spatial heterogeneity, despite preserved gross perivascular morphology. Ventral CSF dynamics showed significant partial correlations with motor severity, whereas selected dorsal flow metrics remained significantly associated with anxiety severity in covariate-adjusted regression analyses. The combined logistic model showed modest diagnostic performance (area under the curve = 0.686), with the highest area under the curve numerically but no statistically significant advantage over individual imaging metrics in paired DeLong comparisons. Conclusion: This framework provides an exploratory neuroimaging reference for moderate-to-advanced, DBS-eligible PD and may support future validation studies and DBS-related investigations.
Background: Vagus nerve stimulation (VNS) is a recognized palliative surgical therapy for drug-resistant epilepsy (DRE). However, optimal postoperative parameter adjustment strategies to maximize efficacy remain an area of active investigation, particularly concerning different etiologies and seizure types. This study was designed to explore the therapeutic efficacy of VNS and postoperative parameter adjustment in patients with DRE. Methods: Eighteen patients with DRE who underwent VNS implantation were retrospectively analyzed. We included patients with focal DRE unsuitable for craniotomy, encephalitis-related DRE, and idiopathic DRE with no identifiable cause. Postoperative stimulation parameters were precisely individualized and adjusted. The efficacy of VNS in controlling seizures was evaluated using the McHugh classification. Results: Eight patients achieved McHugh class IA efficacy (seizure frequency reduction > 80%), seven achieved class IIA efficacy (> 50% reduction), and three achieved class III efficacy (< 50% reduction; IIIA in two and IIIB in one). Conclusion: VNS demonstrated significant therapeutic efficacy in patients with DRE, particularly those with a structural etiology and generalized tonic–clonic seizures. The effect was especially notable in post-traumatic DRE. Postoperative current adjustment proved more complex and influential compared with pulse width and frequency modifications and had a greater impact on seizure control.
Parkinsonu2019s disease is the most prevalent neurodegenerative disease, and its incidence is expected to increase in coming years. This review evaluates the psychometric properties and potential utility of the SENDu2010PD scale in assessing the neuropsychiatric disorders associated with Parkinsonu2019s disease, with a particular focus on their impact on the quality of life of people with the condition. An extensive literature search was conducted from October 1st to 30th 2024, using PubMed, Google Scholar, and ScienceDirect with the keywords: Neuropsychiatric symptoms OR Cognitive impairment OR Cognitive decline AND SENDu2010PD AND Parkinsonu2019s disease OR Parkinsonian syndromes. Inclusion criteria were Englishu2010language articles focused on the psychometric validation, clinical use, or comparison of the SENDu2010PD scale in populations with Parkinsonu2019s disease. Studies unrelated to Parkinsonu2019s disease or assessment tools were excluded. Boolean operators, language filters, and a 10u2010year publication window were applied. The SENDu2010PD scale facilitates early detection and management of neuropsychiatric complications in Parkinsonu2019s disease. Its strength lies in identifying early cognitive impairment, enabling timely interventions such as cognitive rehabilitation and medication adjustments. The SENDu2010PD is a valuable tool that supports ongoing monitoring and treatment optimization for people with Parkinsonu2019s disease, by providing objective evidence of cognitive changes over time.
Grief is a universal yet multifaceted emotional response to loss, profoundly affecting psychological and biological systems. This review aims to examine the neurobiological mechanisms underlying grief, with a particular focus on prolonged grief disorder, a condition characterized by persistent, maladaptive grief symptoms that extend beyond culturally normative grieving periods. This narrative review synthesizes recent findings on the neurobiology of grief. Hormonal dysregulation, such as elevated oxytocin and cortisol levels, plays a significant role in the physiological response to grief. Epigenetic modifications of stressu2010related genes further contribute to individual variability in grief responses. Neural alterations are observed in key brain regions associated with memory, emotion regulation, and attachment, including the amygdala, hippocampus, and prefrontal cortex. Dysfunction of the hypothalamicu2010pituitaryu2010adrenal axis, coupled with disruptions in the default mode network and reward systems, have been implicated in the persistence of pathological grief symptoms. These neurobiological disruptions reflect the interplay among emotional processing, cognitive regulation, and the stress response during grief. By improving our understanding of the biological basis of maladaptive grief responses, these findings provide a foundation for developing targeted therapeutic interventions and guiding future research to better address the needs of individuals experiencing prolonged grief.
Background Parkinsonu2019s Disease (PD) is characterized by motor and nonu2010motor symptoms that can overlap with other movement disorders, complicating accurate diagnosis and monitoring. Wearable technologies, such as smartwatches, offer continuous and objective assessment of motor function, but their clinical utility in multiclass classification and symptom prediction remains underexplored. This study aimed to determine whether smartwatchu2010derived motor features can distinguish idiopathic PD from other movement disorders and whether motor variability is associated with nonu2010motor symptom burden in PD. Methods We analyzed data from the Parkinsonu2019s Disease Smartwatch (PADS) dataset (N = 469), which includes accelerometer and gyroscope signals recorded during 20 standardized motor tasks. For each participant, mean and standard deviation values for each axis were averaged across tasks. Diagnostic group classification was assessed using multinomial logistic regression. Among individuals with idiopathic PD (n = 276), linear regression evaluated associations between motor variability and total nonu2010motor symptom scores from a 30u2010item questionnaire. Results Motor variability features, particularly accelerometer Yu2010axis and gyroscope Xu2010axis standard deviations, significantly differentiated diagnostic groups (pseudo R2 = 0.068). Age, sex, and handedness also contributed. In the PD subgroup, higher accelerometer X and gyroscope X variability were associated with greater nonu2010motor symptom burden, while greater stability in the mediolateral (Y) axis was linked to fewer symptoms (adjusted R2 = 0.0081, p u0026lt; 0.001). Conclusion Smartwatchu2010derived motor variability features can modestly differentiate movement disorder diagnoses and are associated with nonu2010motor symptom severity in PD. Our findings support the complementary use of wearable sensors in clinical assessment and remote monitoring. Our findings also lay the foundation for future integration of wearableu2010derived data into telemedicine workflows.
Background: Parkinson’s Disease (PD) is characterized by motor and non-motor symptoms that can overlap with other movement disorders, complicating accurate diagnosis and monitoring. Wearable technologies, such as smartwatches, offer continuous and objective assessment of motor function, but their clinical utility in multiclass classification and symptom prediction remains underexplored. This study aimed to determine whether smartwatch-derived motor features can distinguish idiopathic PD from other movement disorders and whether motor variability is associated with non-motor symptom burden in PD. Methods: We analyzed data from the Parkinson’s Disease Smartwatch (PADS) dataset ( N = 469), which includes accelerometer and gyroscope signals recorded during 20 standardized motor tasks. For each participant, mean and standard deviation values for each axis were averaged across tasks. Diagnostic group classification was assessed using multinomial logistic regression. Among individuals with idiopathic PD ( n = 276), linear regression evaluated associations between motor variability and total non-motor symptom scores from a 30-item questionnaire. Results: Motor variability features, particularly accelerometer Y-axis and gyroscope X-axis standard deviations, significantly differentiated diagnostic groups (pseudo R 2 = 0.068). Age, sex, and handedness also contributed. In the PD subgroup, higher accelerometer X and gyroscope X variability were associated with greater non-motor symptom burden, while greater stability in the mediolateral (Y) axis was linked to fewer symptoms (adjusted R 2 = 0.0081, p < 0.001). Conclusion: Smartwatch-derived motor variability features can modestly differentiate movement disorder diagnoses and are associated with non-motor symptom severity in PD. Our findings support the complementary use of wearable sensors in clinical assessment and remote monitoring. Our findings also lay the foundation for future integration of wearable-derived data into telemedicine workflows.
Parkinson’s disease is the most prevalent neurodegenerative disease, and its incidence is expected to increase in coming years. This review evaluates the psychometric properties and potential utility of the SEND-PD scale in assessing the neuropsychiatric disorders associated with Parkinson’s disease, with a particular focus on their impact on the quality of life of people with the condition. An extensive literature search was conducted from October 1st to 30th 2024, using PubMed, Google Scholar, and ScienceDirect with the keywords: Neuropsychiatric symptoms OR Cognitive impairment OR Cognitive decline AND SEND-PD AND Parkinson’s disease OR Parkinsonian syndromes. Inclusion criteria were English-language articles focused on the psychometric validation, clinical use, or comparison of the SEND-PD scale in populations with Parkinson’s disease. Studies unrelated to Parkinson’s disease or assessment tools were excluded. Boolean operators, language filters, and a 10-year publication window were applied. The SEND-PD scale facilitates early detection and management of neuropsychiatric complications in Parkinson’s disease. Its strength lies in identifying early cognitive impairment, enabling timely interventions such as cognitive rehabilitation and medication adjustments. The SEND-PD is a valuable tool that supports ongoing monitoring and treatment optimization for people with Parkinson’s disease, by providing objective evidence of cognitive changes over time.
Grief is a universal yet multifaceted emotional response to loss, profoundly affecting psychological and biological systems. This review aims to examine the neurobiological mechanisms underlying grief, with a particular focus on prolonged grief disorder, a condition characterized by persistent, maladaptive grief symptoms that extend beyond culturally normative grieving periods. This narrative review synthesizes recent findings on the neurobiology of grief. Hormonal dysregulation, such as elevated oxytocin and cortisol levels, plays a significant role in the physiological response to grief. Epigenetic modifications of stress-related genes further contribute to individual variability in grief responses. Neural alterations are observed in key brain regions associated with memory, emotion regulation, and attachment, including the amygdala, hippocampus, and prefrontal cortex. Dysfunction of the hypothalamic-pituitary-adrenal axis, coupled with disruptions in the default mode network and reward systems, have been implicated in the persistence of pathological grief symptoms. These neurobiological disruptions reflect the interplay among emotional processing, cognitive regulation, and the stress response during grief. By improving our understanding of the biological basis of maladaptive grief responses, these findings provide a foundation for developing targeted therapeutic interventions and guiding future research to better address the needs of individuals experiencing prolonged grief.
Parkinson’s Disease (PD) is a progressive neurological disorder marked by motor and non-motor symptoms. Deep Brain Stimulation (DBS) is a proven surgical treatment for advanced PD, yet access and utilization remain unequal—particularly along gender lines. Patient education plays a vital role in optimizing DBS outcomes and addressing these disparities. This review analyzes existing literature on educational practices related to DBS in PD, focusing on their impact on patient outcomes, engagement, and healthcare equity. It also examines the role of gender and the contributions of nursing staff in delivering education and support. While structured educational programs do not directly improve clinical outcomes, they significantly enhance patient satisfaction and informed decision- making. Tailored counseling and nurse-led psychoeducation reduce anxiety and address informational gaps. Gender disparities persist, with women less likely to undergo DBS, partly due to lack of awareness and biased referral patterns. Patient-centered education and psychoeducational interventions—particularly those led by nursing staff—are essential to improving care quality and satisfaction in DBS for PD. Addressing gender-based barriers and standardizing education delivery can promote more equitable and effective treatment outcomes.
