BackgroundThe purpose of this study was to compare the diagnostic performance of isolated-check visual evoked potential (icVEP) with that of retinal ganglion cell-inner plexiform layer (GCILP) analysis using optical coherence tomography (OCT).MethodsA total of 45 patients were enrolled: 25 patients with open-angle glaucoma and 20 healthy patients. All patients underwent a complete ophthalmological examination. Moreover, the OCT examination was used to analyze the structures of the GCIPL. The icVEP technique was used to detect the transmission function of the magnocellular pathway, which is mainly managed by the retinal ganglion cells. The quantitative and qualitative comparisons between the diagnostic power of GCIPL analysis and that of icVEP were performed. The areas under the receiver operating characteristic curves (AUC) of GCIPL analysis and icVEP were compared using the Clarke-Pearson method. The sensitivity and specificity of the two techniques were analyzed and compared using the McNemar test.ResultsWith the quantitative comparison, the AUC of icVEP (AUC = 0.892) was higher than that of GCIPL analysis (AUC = 0.814). However, there was no statistical significance between the AUCs of icVEP and GCIPL (P > 0.05). With the qualitative comparison, the sensitivity of icVEP was 80%, and its specificity was 90%. The sensitivity of GCIPL analysis was 72%, and its specificity was 85%. There was no significant difference between the sensitivitiesor specificities of icVEP and GCIPL analysis (P > 0.05). Moreover, 30 (66.67%) eyeshad similar resultsbetween icVEP and GCIPL analysis, and 15 (33.33%) eyes had different results (7 eyes had abnormal results with GCIPL analysisbut normal results with icVEP, and8 eyes had normal results with GCIPL analysisbut abnormal results with icVEP).ConclusionsThe diagnostic power of icVEP was close to that of GCIPL analysis whether the comparison was based on the qualitative or quantitative data.
T cell exhaustion caused by mitochondrial dysfunction is the major obstacle of T cells‐based cancer immunotherapy. Besides exhausted T cells, the insufficient major histocompatibility complex class I (MHC I) on tumor cells leads to inefficient T cell recognition of tumor cells, compromising therapeutic efficacy. Therapeutic platform to regulate T cell exhaustion and MHC I expression for boosting T cells‐based cancer immunotherapy has not been realized up to date. Herein, an injectable hydrogel is designed to simultaneously tune T cell exhaustion and MHC I expression for amplified cancer immunotherapy. The hydrogel is in situ constructed in tumor site by utilizing oxidized sodium alginate‐modified tumor cell membrane vesicle (O‐TMV) as a gelator, where axitinib is encapsulated in the lipid bilayer of O‐TMV while 4‐1BB antibody and proprotein convertase subtilisin/kexin type 9 inhibitor PF‐06446846 nanoparticles are present in the cavities of hydrogel. After immune response trigged by O‐TMV antigen, the 4‐1BB antibody‐promoted T cell mitochondrial biogenesis and the axitinib‐lowered hypoxia synergistically reverse T cell exhaustion while the PF‐06446846‐amplified MHC I expression facilitates T cell recognition of tumor cells, demonstrating a powerful immunotherapeutic efficacy. This strategy on reprograming T cell exhaustion and improving T cell potency offers new concept for T cells‐based cancer immunotherapy.
Background The LiBackpack is a recently developed backpack light detection and ranging (LiDAR) system that combines the flexibility of human walking with the nearby measurement in all directions to provide a novel and efficient approach to LiDAR remote sensing, especially useful for forest structure inventory. However, the measurement accuracy and error sources have not been systematically explored for this system. Method In this study, we used the LiBackpack D-50 system to measure the diameter at breast height (DBH) for a Pinus sylvestris tree population in the Saihanba National Forest Park of China, and estimated the accuracy of LiBackpack measurements of DBH based on comparisons with manually measured DBH values in the field. We determined the optimal vertical slice thickness of the point cloud sample for achieving the most stable and accurate LiBackpack measurements of DBH for this tree species, and explored the effects of different factors on the measurement error. Result 1) A vertical thickness of 30 cm for the point cloud sample slice provided the highest fitting accuracy (adjusted R2 = 0.89, Root Mean Squared Error (RMSE) = 20.85 mm); 2) the point cloud density had a significant negative, logarithmic relationship with measurement error of DBH and it explained 35.1% of the measurement error; 3) the LiBackpack measurements of DBH were generally smaller than the manually measured values, and the corresponding measurement errors increased for larger trees; and 4) by considering the effect of the point cloud density correction, a transitional model can be fitted to approximate field measured DBH using LiBackpack- scanned value with satisfactory accuracy (adjusted R2 = 0.920; RMSE = 14.77 mm), and decrease the predicting error by 29.2%. Our study confirmed the reliability of the novel LiBackpack system in accurate forestry inventory, set up a useful transitional model between scanning data and the traditional manual-measured data specifically for P. sylvestris, and implied the applicable substitution of this new approach for more species, with necessary parameter calibration.
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