Background To identify a radiomics signature to predict local recurrence in patients with non-metastatic T4 nasopharyngeal carcinoma (NPC). Methods A total of 737 patients from Sun Yat-sen University Cancer Center (training cohort: n = 360; internal validation cohort: n = 120) and Wuzhou Red Cross Hospital (external validation cohort: n = 257) underwent feature extraction from the largest axial area of the tumor on pretreatment magnetic resonance imaging scans. Feature selection was based on the prognostic performance and feature stability in the training cohort. Radscores were generated using the Cox proportional hazards regression model with the selected features in the training cohort and then validated in the internal and external validation cohorts. We also constructed a nomogram for predicting local recurrence-free survival (LRFS). Findings Eleven features were selected to construct the Radscore, which was significantly associated with LRFS. For the training, internal validation, and external validation cohorts, the Radscore (C-index: 0.741 vs. 0.753 vs. 0.730) outperformed clinical prognostic variables (C-index for primary gross tumor volume: 0.665 vs. 0.672 vs. 0.577; C-index for age: 0.571 vs. 0.629 vs. 0.605) in predicting LRFS. The generated radiomics nomogram, which integrated the Radscore and clinical variables, exhibited a satisfactory prediction performance (C-index: 0.810 vs. 0.807 vs. 0.753). The nomogram-defined high-risk group had a shorter LRFS than did the low-risk group (5-year LRFS: 73.6% vs. 95.3%, P < .001; 79.6% vs 95.8%, P = .006; 85.7% vs 96.7%, P = .005). Interpretation The Radscore can reliably predict LRFS in patients with non-metastatic T4 NPC, which might guide individual treatment decisions. Fund This study was funded by the Health & Medical Collaborative Innovation Project of Guangzhou City, China.
We have reported previously that bone marrow mesenchymal stem cell (MSC)-derived neural network scaffold not only survived in the injury/graft site of spinal cord but also served as a "neuronal relay" that was capable of improving the limb motor function in a complete spinal cord injury (SCI) rat model. It remained to be explored whether such a strategy was effective for repairing the large spinal cord tissue loss as well as restoring motor function in larger animals. We have therefore extended in this study to construct a canine MSC-derived neural network tissue in vitro with the aim to evaluate its efficacy in treating adult beagle dog subjected to a complete transection of the spinal cord. The results showed that after co-culturing with neurotropin-3 overexpressing Schwann cells in a gelatin sponge scaffold for 14 days, TrkC overexpressing MSCs differentiated into neuron-like cells. In the latter, some cells appeared to make contacts with each other through synapse-like structures with trans-synaptic electrical activities. Remarkably, the SCI canines receiving the transplantation of the MSC-derived neural network tissue demonstrated a gradual restoration of paralyzed limb motor function, along with improved electrophysiological presentation when compared with the control group. Magnetic resonance imaging and diffusion tensor imaging showed that the canines receiving the MSC-derived neural network tissue exhibited robust nerve tract regeneration in the injury/graft site. Histological analysis showed that some of the MSC-derived neuron-like cells had survived in the injury/graft site up to 6.5 months. Implantation of MSC-derived neural network tissue significantly improved the microenvironment of the injury/graft site. It is noteworthy that a variable number of them had integrated with the regenerating corticospinal tract nerve fibers and 5-HT nerve fibers through formation of synapse-like contacts. The results suggest that the transplanted MSC-derived neural network tissue may serve as a structural and functional "neuronal relay" to restore the paralyzed limb motor function in the canine with complete SCI.
Key Points Question Could a prognostic nomogram that integrates the TNM staging system with other critical variables accurately predict overall survival and guide treatment in patients with nonmetastatic nasopharyngeal carcinoma? Findings In this cohort study of 8093 patients with nasopharyngeal carcinoma, a nomogram was developed and validated to reliably estimate overall survival, which provided significantly better discrimination than the TNM staging system. This nomogram identified 4 risk groups with differential OS rates; these 4 risk groups were associated with the efficacy of different treatment regimens. Meaning These finding suggest that this nomogram could enable individualized prognostication of overall survival and guide risk-adapted treatment for patients with nonmetastatic nasopharyngeal carcinoma.
Tissue engineering–based neural construction holds promise in providing organoids with defined differentiation and therapeutic potentials. Here, a bioengineered transplantable spinal cord–like tissue (SCLT) is assembled in vitro by simulating the white matter and gray matter composition of the spinal cord using neural stem cell–based tissue engineering technique. Whether the organoid would execute targeted repair in injured spinal cord is evaluated. The integrated SCLT, assembled by white matter–like tissue (WMLT) module and gray matter–like tissue (GMLT) module, shares architectural, phenotypic, and functional similarities to the adult rat spinal cord. Organotypic coculturing with the dorsal root ganglion or muscle cells shows that the SCLT embraces spinal cord organogenesis potentials to establish connections with the targets, respectively. Transplantation of the SCLT into the transected spinal cord results in a significant motor function recovery of the paralyzed hind limbs in rats. Additionally, targeted spinal cord tissue repair is achieved by the modular design of SCLT, as evidenced by an increased remyelination in the WMLT area and an enlarged innervation in the GMLT area. More importantly, the pro‐regeneration milieu facilitates the formation of a neuronal relay by the donor neurons, allowing the conduction of descending and ascending neural inputs.
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