Chaichana, Kaisorn

AbstractMicroglia have fundamental roles in health and disease; however, effects of age, sex, and genetic factors on human microglia have not been fully explored. We applied bulk and single‐cell approaches to comprehensively characterize human microglia transcriptomes and their associations with age, sex, and APOE. We identified a novel microglial signature, characterized its expression in bulk tissue and single‐cell microglia transcriptomes. We discovered microglial co‐expression network modules associated with age, sex, and APOE‐ε4 that are enriched for lipid and carbohydrate metabolism genes. Integrated analyses of modules with single‐cell transcriptomes revealed significant overlap between age‐associated module genes and both pro‐inflammatory and disease‐associated microglial clusters. These modules and clusters harbor known neurodegenerative disease genes including APOE, PLCG2, and BIN1. Meta‐analyses with published bulk and single‐cell microglial datasets further supported our findings. Thus, these data represent a well‐characterized human microglial transcriptome resource and highlight age, sex, and APOE‐related microglial immunometabolism perturbations with potential relevance in neurodegeneration.

Abstract BACKGROUND Brain mapping is the most reliable intraoperative tool for identifying surrounding functional cortical and subcortical brain parenchyma. Brain mapping procedures are nuanced and require a multidisciplinary team and a well-trained neurosurgeon. Current training methodology involves real-time observation and operation, without widely available surgical simulation. OBJECTIVE To develop a patient-specific, anatomically accurate, and electrically responsive biomimetic 3D-printed model for simulating brain mapping. METHODS Imaging data were converted into a 2-piece inverse 3D-rendered polyvinyl acetate shell forming an anatomically accurate brain mold. Functional and diffusion tensor imaging data were used to guide wire placement to approximate the projection fibers from the arm and leg areas in the motor homunculus. Electrical parameters were generated, and data were collected and processed to differentiate between the 2 tracts. For validation, the relationship between the electrical signal and the distance between the probe and the tract was quantified. Neurosurgeons and trainees were interviewed to assess the validity of the model. RESULTS Material testing of the brain component showed an elasticity modulus of 55 kPa (compared to 140 kPa of cadaveric brain), closely resembling the tactile feedback a live brain. The simulator's electrical properties approximated that of a live brain with a voltage-to-distance correlation coefficient of r 2 = 0.86. Following 32 neurosurgeon interviews, ∼96% considered the model to be useful for training. CONCLUSION The realistic neural properties of the simulator greatly improve representation of a live surgical environment. This proof-of-concept model can be further developed to contain more complicated tractography, blood and cerebrospinal fluid circulation, and more in-depth feedback mechanisms.

OCT-based quantitative tissue optical properties imaging is a promising technique for intraoperative brain cancer assessment. The attenuation coefficient analysis relies on the depth-dependent OCT intensity profile, thus sensitive to tissue surface positions relative to the imaging beam focus. However, it is almost impossible to maintain a steady tissue surface during intraoperative imaging due to the patient’s arterial pulsation and breathing, the operator’s motion, and the complex tissue surface geometry of the surgical cavity. In this work, we developed an intraoperative OCT imaging probe with a surface-tracking function to minimize the quantification errors in optical attenuation due to the tissue surface position variations. A compact OCT imaging probe was designed and engineered to have a long working distance of ∼ 41 mm and a large field of view of 4 × 4 mm2 while keeping the probe diameter small (9 mm) to maximize clinical versatility. A piezo-based linear motor was integrated with the imaging probe and controlled based upon real-time feedback of tissue surface position inferred from OCT images. A GPU-assisted parallel processing algorithm was implemented, enabling detection and tracking of tissue surface in real-time and successfully suppressing more than 90% of the typical physiologically induced motion range. The surface-tracking intraoperative OCT imaging probe could maintain a steady beam focus inside the target tissue regardless of the surface geometry or physiological motions and enabled to obtain tissue optical attenuation reliably for assessing brain cancer margins in challenging intraoperative settings.