Intraoperative and spatiotemporal monitoring of neuroinflammatory indices during brain-computer interface (BCI) implantation is essential for ensuring safety and efficacy of the procedure. Current biomolecular detection approaches are unable to obtain spatiotemporally resolved inflammatory profiling, which is important for guiding the placement of microelectrodes intraoperatively. This study presents an intraoperative spatiotemporal acute inflammation detector (ISAID) that harnesses droplet-based sampling and multiplexed titanium oxynitride (TiNO) plasmonic biosensing to assess local inflammation during the insertion of intracortical microelectrodes. Through freestanding sampling droplets and fine-tuned TiNO-based biosensors, the ISAID achieved precise, sensitive, and integrated sampling to biosensing for cytokine detection with a spatial resolution down to 610 mu m and a fast equivalent bioassay time of 1.25 min. The proposed system also allows multiple ISAID biosensing modes, enabling both spatial inflammation mapping and multi-cytokine analysis. Quantitative analyses of inflammatory cytokines with in vivo mouse models demonstrate the accuracy and practical advantages of the system.

Abstract Objectives To develop and validate nomograms combining radiomics and semantic features to identify the invasiveness and histopathological risk stratification of thymic epithelial tumors (TET) using contrast-enhanced CT. Methods This retrospective multi-center study included 224 consecutive cases. For each case, 6764 intratumor and peritumor radiomics features and 31 semantic features were collected. Multi-feature selections and decision tree models were performed on radiomics features and semantic features separately to select the most important features for Masaoka–Koga staging and WHO classification. The selected features were then combined to create nomograms for the two systems. The performance of the radiomics model, semantic model, and combined model was evaluated using the area under the receiver operating characteristic curves (AUCs). Results One hundred eighty-seven cases (56.5 years ± 12.3, 101 men) were included, with 62 cases as the external test set. For Masaoka–Koga staging, the combined model, which incorporated five peritumor radiomics features and four semantic features, showed an AUC of 0.958 (95% CI: 0.912–1.000) in distinguishing between early-stage (stage I/II) and advanced-stage (III/IV) TET in the external test set. For WHO classification, the combined model incorporating five peritumor radiomics features and two semantic features showed an AUC of 0.857 (0.760–0.955) in differentiating low-risk (type A/AB/B1) and high-risk (B2/B3/C) TET. The combined models showed the most effective predictive performance, while the semantic models exhibited comparable performance to the radiomics models in both systems (p > 0.05). Conclusion The nomograms combining peritumor radiomics features and semantic features could help in increasing the accuracy of grading invasiveness and risk stratification of TET. Critical relevance statement Peripheral invasion and histopathological type are major determinants of treatment and prognosis of TET. The integration of peritumoral radiomics features and semantic features into nomograms may enhance the accuracy of grading invasiveness and risk stratification of TET. Key Points Peritumor region of TET may suggest histopathological and invasive risk. Peritumor radiomic and semantic features allow classification by Masaoka–Koga staging (AUC: 0.958). Peritumor radiomic and semantic features enable the classification of histopathological risk (AUC: 0.857). Graphical Abstract

Since the brain structure of neonatal rats was not fully formed during the first 4 days, it cannot be detected using ultrasound. The objective of this study was to investigate the use of ultrasound to guide puncture in the normal coronal brain structure and determine the puncture depth of the location of the cortex, hippocampus, lateral ventricle, and striatum of newborn rats of 5-15 days. The animal was placed in a prone position. The specific positions of the cortex, hippocampus, lateral ventricle, and striatum were measured under ultrasound. Then, the rats were punctured with a stereotaxic instrument, and dye was injected. Finally, the brains of rats were taken to make frozen sections to observe the puncture results. By ultrasound, the image of the cortex, hippocampus, lateral ventricle, and striatum of the rat can be obtained and the puncture depth of the cortex (8 days: 1.02 ± 0.12, 10 days: 1.02 ± 0.08, 13 days: 1.43 ± 0.05), hippocampus (8 days: 2.63 ± 0.07, 10 days: 2.77 ± 0.14, 13 days: 2.82 ± 0.09), lateral ventricle (8 days: 2.08 ± 0.04, 10 days: 2.26 ± 0.03, 13 days: 2.40 ± 0.06), and corpus striatum (8 days: 4.57 ± 0.09, 10 days: 4.94 ± 0.31, 13 days: 5.13 ± 0.10) can be accurately measured. The rat brain structure and puncture depth changed with the age of the rats. Ultrasound technology can not only clarify the brain structure characteristics of 5-15-day-old rats but also guide the puncture and injection of the rat brain structure. The results of this study laid the foundation for the future use of ultrasound in experimental animal models of neurological diseases.

BACKGROUND:Thyroid-associated ophthalmopathy (TAO) is an autoimmune orbital disease characterized by edema of extraocular muscles (EOMs). PURPOSE:To characterize the inflammation of EOMs in patients with TAO before and after radiation therapy using apparent diffusion coefficient (ADC) and to analyze the correlation between ADC and clinical activity of TAO. MATERIAL AND METHODS:The ADCs of superior rectus (SR), inferior rectus (IR), medial rectus (MR), and lateral rectus (LR) muscles were measured in 52 eyes of 26 patients with TAO before and three months after orbital radiation therapy. In addition, 38 eyes of 20 healthy volunteers were included. The clinical activity score (CAS) was evaluated. The ADC maps were reconstructed and measured on the coronal diffusion-weighted imaging (DWI) sequence and calculated in mm2/s. RESULTS:The mean ADCs of EOMs before treatment were 1.42 ± 0.23 in SR, 1.37 ± 0.23 in IR, 1.41 ± 0.21 in MR, and 1.28 ± 0.25 in LR. The mean ADCs after treatment were 1.27 ± 0.18, 1.22 ± 0.26, 1.30 ± 0.22, and 1.15 ± 0.21, respectively. The ADCs were significantly decreased after treatment (all P < 0.001). The ADCs of patients with TAO were significantly higher than those of controls. There was a statistically significant correlation between the mean ADCs and the CAS in each patient with TAO both before and after treatment (before: r = 0.520; P < 0.001; after: r = 0.625; P < 0.001). CONCLUSION:The ADC values of EOMs can be exploited as a quantitative indicator to evaluate the clinical activity and monitor the therapeutic responses of patients with TAO.