Introduction: Inflammatory processes and neurodegeneration are common features of Alzheimer's disease (AD). The systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) are easily accessible, cost-effective prognostic indicators of inflammation status. We assessed the diagnostic value of SII and compared the efficacies of NLR, PLR, and SII in predicting AD severity. Materials and Methods: Between January 2021 and December 2022, this prospective, cross-sectional clinical study included 175 patients with AD and 61 controls. SII, NLR, and PLR were calculated. Results: Age, white blood cell and lymphocyte counts, and NLR and PLR values were significantly different between the patient and control groups ( P <.05). Age, hemoglobin, neutrophil, NLR, and SII values were significantly different among dementia severity subgroups ( P <.05). Compared with PLR and SII, NLR was more strongly correlated with dementia severity. In the analysis of adjusted data by gender, it was found that hemoglobin level is significantly negatively associated with dementia severity in males, while in females, age and PLR are significantly positively associated with dementia severity, and lymphocyte count and SII are negatively associated. Conclusion: SII, a novel inflammatory marker, was associated with dementia severity in patients with AD. Compared with PLR and SII, NLR was more strongly correlated with dementia severity. In future studies with larger populations, SII and NLR values can be used to determine dementia severity and establish follow-up plans for patients with high dementia risk.

Background/Objectives: Parkinson’s disease (PD) is a progressive neurodegenerative disorder that requires early and accurate diagnosis. This study aimed to classify individuals with and without PD using volumetric brain MRI data and to improve model interpretability using explainable artificial intelligence (XAI) techniques. Methods: This retrospective study included 79 participants (39 PD patients, 40 controls) recruited at Inonu University Turgut Ozal Medical Center between 2013 and 2025. A deep neural network (DNN) was developed using a multilayer perceptron architecture with six hidden layers and ReLU activation functions. Seventeen volumetric brain features were used as the input. To ensure robust evaluation and prevent overfitting, a stratified five-fold cross-validation was applied, maintaining class balance in each fold. Model transparency was explored using two complementary XAI techniques: the Contrastive Explanation Method (CEM) and Local Interpretable Model-Agnostic Explanations (LIME). CEM highlights features that support or could alter the current classification, while LIME provides instance-based feature attributions. Results: The DNN model achieved high diagnostic performance with 94.1% accuracy, 98.3% specificity, 90.2% sensitivity, and an AUC of 0.97. The CEM analysis suggested that reduced hippocampal volume was a key contributor to PD classification (–0.156 PP), whereas higher volumes in the brainstem and hippocampus were associated with the control class (+0.035 and +0.150 PP, respectively). The LIME results aligned with these findings, revealing consistent feature importance (mean = 0.1945) and faithfulness (0.0269). Comparative analyses showed different volumetric patterns between groups and confirmed the DNN’s superiority over conventional machine learning models such as SVM, logistic regression, KNN, and AdaBoost. Conclusions: This study demonstrates that a deep learning model, enhanced with CEM and LIME, can provide both high diagnostic accuracy and interpretable insights for PD classification, supporting the integration of explainable AI in clinical neuroimaging.

Background The etiology of Parkinson’s disease (PD) is not well known and there is increasing evidence that oxidative stress also plays an important role in its pathogenesis. Salusins alpha (salusin-α) and beta (salusin-β) affect the central nervous system, vasculature, and kidneys to increase the inflammatory response in endothelial cells, stimulate oxidative stress, and increase monocyte–endothelial adhesion. Neuroinflammation and oxidative stress play roles in the etiopathogenesis of PD. Purpose To investigate whether salusin-α and -β are related to PD and whether they are correlated with the development of atherosclerosis, body mass index, disease duration, and the Parkinson’s Hoehn and Yahr stage. Results The low-density lipoprotein cholesterol (LDL-C), total cholesterol, and salusin-β levels were significantly lower and age was significantly higher in Parkinson patients compared to healthy controls (ρ < 0.005). We found a negative linear correlation between salusin-β and the Hoehn and Yahr stage (ρ < 0.001, r = –0.515) in the patients. Conclusions There was a relationship between salusin-β and PD and a correlation between the salusin-β levels and Parkinson’s stage. A possible underlying disease mechanism is an increase in oxidative stress and decrease in neuroprotective effects due to low salusin-β levels. Therefore, the effects of salusin-β in treating Parkinson disease should be evaluated. Further studies are needed to understand the effects of salusin-β treatment on preventing or slowing the course of PD.

Objectives: This study aimed to assess whether the C-reactive protein/albumin ratio (CAR) is a risk factor for trigeminal neuralgia (TN) development and the relationship between the CAR and TN pain frequency. Patients and methods: In this retrospective study, 100 patients (51 females, 49 males; mean age: 58.6±14.1 years; range, 31 to 88 years) with idiopathic TN and 70 healthy controls (38 females, 32 males; mean age: 54.1±15.7 years; range, 21 to 89 years) were included between January 2020 and December 2022. Patients were divided into two groups by weekly and monthly pain frequency. The laboratory findings and CARs were compared. Results: The CAR values were significantly different between the patient and control groups (p<0.05) and were significantly different among TN subgroups divided according to attack frequency (p<0.05). Conclusion: Since there was a significant relationship between TN and CAR as a prognostic predictor, this relationship demonstrated once again that inflammation plays a role in the etiopathogenesis of TN. As opposed to previous studies that investigated the effect of only inflammation, the effects of both inflammation and malnutrition could be investigated by evaluating CAR in this study.

Rosai-Dorfman disease (RDD) is a benign histiocytosis with unknown etiology. It generally occurs in cervical lymph nodes. Isolated central nervous system (CNS) RDD is very rare in the literature. We reported a case of no systemic involvement Rosai-Dorfmann which is rarely seen and shows CNS involvement by mimicking meningioma. A 32-year-old man presented with diplopia and a headache he has been experiencing for the past two years. His neurological examination showed left facial paresthesia, consistent with trigeminal nerve trace. Tendon reflexes were increased at the right side and the right plantar reflex was extensor. Brain magnetic resonance imaging demonstrated irregularly shaped, tumor-like lesions in the bilateral cerebellopontin area that were compressing pons. Rosai-Dorfman disease can be differentiated from IgG4 related disease (IgG4-RD) by its characteristic features such as plasma cell density and emperipolesis seen in its histopathology. Rosai-Dorfman disease can be confused with other diseases radiologically and histopathologically, especially the IgG4-RD, so be careful about differential diagnosis.