ABSTRACT
Pancreatic cancer (PC) is a highly malignant cancer characterized by poor prognosis, high heterogeneity, and intricate heterocellular systems. Selecting an appropriate experimental model for studying its progression and treatment is crucial. Patient-derived models provide a more accurate representation of tumor heterogeneity and complexity compared to cell line-derived models. This review initially presents relevant patient-derived models, including patient-derived xenografts (PDXs), patient-derived organoids (PDOs), and patient-derived explants (PDEs), which are essential for studying cell communication and pancreatic cancer progression. We have emphasized the utilization of these models in comprehending intricate intercellular communication, drug responsiveness, mechanisms underlying tumor growth, expediting drug discovery, and enabling personalized medical approaches. Additionally, we have comprehensively summarized single-cell analyses of these models to enhance comprehension of intercellular communication among tumor cells, drug response mechanisms, and individual patient sensitivities.
Subject(s)
Organoids , Pancreatic Neoplasms , Single-Cell Analysis , Tumor Microenvironment , Humans , Pancreatic Neoplasms/genetics , Pancreatic Neoplasms/pathology , Pancreatic Neoplasms/metabolism , Single-Cell Analysis/methods , Animals , Organoids/metabolism , Tumor Microenvironment/genetics , Cell Communication/genetics , Precision MedicineABSTRACT
Although Freezing of gait (FOG) is one of the most frustrating phenomena for people with Parkinson's Disease (PD), especially in their advanced stage, it is one of the least explained syndromes. The current studies only showed beta oscillations existed in frontal cortex-basal ganglia networks. Further studies need to be carried out. However, simultaneously recording neuro-electrophysiologic signals during walking is always a challenge, especially for Electroencephalogram (EEG) and Local Field Potential (LFP). This paper demonstrated a Virtual Reality (VR) based system which can trigger FOG and record biological signals at the same time. Moreover, the utilisation of VR will significantly decrease space requirements. It will provide a safer and more convenient evaluation environment for future participants. One participant with PD helped to validate the feasibility of the system. The result showed that both EEG and LFP could be recorded at the same time with trigger markers. This system design can be used to trigger freezing episodes in the controlled environment, differentiate subtypes of gait difficulties, and identify neural signatures associated with freezing episodes.Clinical relevance - This paper proposed a VR-based comprehensive FOG neuro-electrophysiologic evaluation system for people with PD. It had the advantages of minimum space requirement and wireless LFP data collection without externalised leads. This paper was to indicate a larger study which would formally recruit larger populations with PD and FOG. Future studies would explore FOG-related brain network coherence.
