Publications by authors named "S Q Liang"

Objective: Since the emergence of the Pipeline Embolization Device (PED), its off-label use has significantly improved the treatment effectiveness of complex intracranial aneurysms, including the treatment of recurrent aneurysms. Although PED is effective in this situation, there is still a lack of evidence-based medicine for its role in recurrent aneurysms after stent-assisted coiling. The aim of this study is to evaluate the safety and efficacy of PED treatment for recurrent aneurysms after stent-assisted coiling.

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Assay for Transposase-Accessible Chromatin with sequencing (ATAC-seq) is a powerful, high-throughput technique for assessing chromatin accessibility and understanding epigenomic regulation. Neutrophils, as a crucial leukocyte type in immune responses, undergo substantial chromatin architectural changes during differentiation and activation, which significantly impact the gene expression necessary for their functions. ATAC-seq has been instrumental in uncovering key transcription factors in neutrophil maturation, revealing pathogen-specific epigenomic signatures, and identifying therapeutic targets for autoimmune diseases.

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We report the canonical properties of the Bose-Einstein condensation of polaritons in the weak coupling regime, seen previously in many low-temperature experiments, at room temperature in a GaAs/AlGaAs structure. These effects include a nonlinear energy shift of the polaritons, showing that they are not noninteracting photons, and dramatic line narrowing due to coherence, giving coherent emission with a spectral width of 0.24 meV at room temperature with no external stabilization.

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Background: Lung adenocarcinoma (LUAD) is associated with high morbidity and mortality rates. Increasing evidence indicates that neutrophil extracellular traps (NETs) play a critical role in tumor progression, metastasis and immunosuppression in the LUAD tumor microenvironment (TME). Nevertheless, the use of NET formation-related genes (NFRGs) to predict LUAD patient survival and response to immunotherapy has not been explored.

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Background: Knee osteoarthritis (KOA) constitutes the prevailing manifestation of arthritis. Radiographs function as a common modality for primary screening; however, traditional X-ray evaluation of osteoarthritis confronts challenges such as reduced sensitivity, subjective interpretation, and heightened misdiagnosis rates. The objective of this investigation is to enhance the validation and optimization of accuracy and efficiency in KOA assessment by utilizing fusion deep learning techniques.

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