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The mechanism underlying neurogenesis during embryonic spinal cord development involves a specific ligand/receptor interaction, which may be help guide neuroengineering to boost stem cell-based neural regeneration for the structural and functional repair of spinal cord injury. Herein, we hypothesized that supplying spinal cord defects with an exogenous neural network in the NT-3/fibroin-coated gelatin sponge (NF-GS) scaffold might improve tissue repair efficacy. To test this, we engineered tropomyosin receptor kinase C (TrkC)-modified neural stem cell (NSC)-derived neural network tissue with robust viability within an NF-GS scaffold. When NSCs were genetically modified to overexpress TrkC, the NT-3 receptor, a functional neuronal population dominated the neural network tissue. The pro-regenerative niche allowed the long-term survival and phenotypic maintenance of the donor neural network tissue for up to 8 weeks in the injured spinal cord. Additionally, host nerve fibers regenerated into the graft, making synaptic connections with the donor neurons. Accordingly, motor function recovery was significantly improved in rats with spinal cord injury (SCI) that received TrkC-modified NSC-derived neural network tissue transplantation. Together, the results suggested that transplantation of the neural network tissue formed in the 3D bioactive scaffold may represent a valuable approach to study and develop therapies for SCI., Graphical abstract Scheme 1. A neurotrophin-3 (NT-3) sustained-release bioscaffold supports the formation of tyrosine kinase receptor C (TrkC)-modified neural stem cell-derived neural network tissue with efficacy in repairing spinal cord injury.Image 1, Highlights • A NT-3 sustained-release scaffold confers a microenvironment partially simulating the developmental spinal cord. • The NT-3 microenvironment boosts neuronal differentiation of TrkC-modified NSCs by interactions between ligand and receptor. • TrkC-NSCs is self-organized into a neural network tissue with typical neural excitability in 3D bioactive scaffold in vitro. • The grafted neural network tissue can survive and maintain neural property, and improve motor function of paralyzed rats.

SUMMARY Latently infected T cells able to reinitiate viral propagation throughout the body remain a major barrier to curing HIV. Distinguishing between latently infected cells and uninfected cells will advance efforts for viral eradication. HIV decision-making between latency and active replication is stochastic, and drug cocktails that increase bursts of viral gene expression enhance reactivation from latency. Here, we show that a larger host-cell size provides a natural cellular mechanism for enhancing burst size of viral expression and is necessary to destabilize the latent state and bias viral decision-making. Latently infected Jurkat and primary CD4+ T cells reactivate exclusively in larger activated cells, while smaller cells remain silent. In addition, reactivation is cell-cycle dependent and can be modulated with cell-cycle-arresting compounds. Cell size and cell-cycle dependent decision-making of viral circuits may guide stochastic design strategies and applications in synthetic biology and may provide important determinants to advance diagnostics and therapies., In Brief Bohn-Wippert et al. investigate reactivation of T cells latently infected with HIV. They discover that only larger cells exit latency, while smaller cells remain silent. Viral expression bursts are cell size and cell-cycle dependent, presenting dynamic cell states, capable of active control, as sources of viral fate determination., Graphical Abstract

Background: Early failure of cancer treatment generally indicates a poor prognosis. Here, we aim to develop and validate a pre-treatment nomogram to predict early metachronous metastasis (EMM) in nasopharyngeal carcinoma (NPC). Methods: From 2009 to 2015, a total of 9461 patients with NPC (training cohort: n = 7096; validation cohort: n = 2365) were identified from an institutional big-data research platform. EMM was defined as time to metastasis within 2 years after treatment. Early metachronous distant metastasis-free survival (EM-DMFS) was the primary endpoint. A nomogram was established with the significant prognostic factors for EM-DMFS determined by multivariate Cox regression analyses in the training cohort. The Harrell Concordance Index (C-index), area under the receiver operator characteristic curve (AUC), and calibration curves were applied to evaluate this model. Results: EMM account for 73.5% of the total metachronous metastasis rate and is associated with poor long-term survival in NPC. The final nomogram, which included six clinical variables, achieved satisfactory discriminative performance and significantly outperformed the traditional tumor–node–metastasis (TNM) classification for predicting EM-DMFS: C-index: 0.721 versus 0.638, p Conclusion: Our established nomogram can reliably predict EMM in patients with NPC and might aid in formulating risk-adapted treatment decisions and personalized patient follow-up strategies.

Tissue engineering produces constructs with defined functions for the targeted treatment of damaged tissue. A complete spinal cord injury (SCI) model is generated in canines to test whether in vitro constructed neural network (NN) tissues can relay the excitatory signal across the lesion gap to the caudal spinal cord. Established protocols are used to construct neural stem cell (NSC)‐derived NN tissue characterized by a predominantly neuronal population with robust trans‐synaptic activities and myelination. The NN tissue is implanted into the gap immediately following complete transection SCI of canines at the T10 spinal cord segment. The data show significant motor recovery of paralyzed pelvic limbs, as evaluated by Olby scoring and cortical motor evoked potential (CMEP) detection. The NN tissue survives in the lesion area with neuronal phenotype maintenance, improves descending and ascending nerve fiber regeneration, and synaptic integration with host neural circuits that allow it to serve as a neuronal relay to transmit excitatory electrical signal across the injured area to the caudal spinal cord. These results suggest that tissue‐engineered NN grafts can relay the excitatory signal in the completely transected canine spinal cord, providing a promising strategy for SCI treatment in large animals, including humans., In vitro constructed engineered neural network tissue, characterized by a neuronal population with robust trans‐synaptic activities, can survive within the completely transected canine spinal cord, integrate with host neural circuits, and serve as a neuronal relay to transmit excitatory electrical signals across the injured area to the caudal spinal cord, leading to significant motor recovery within the paralyzed pelvic limbs.

In this paper, we study how pixel size influences energy resolution for a proposed pixelated detector---a high sensitivity, low cost, and real-time radon monitor based on \textit{Topmetal-${II}^-$} time projection chamber (TPC). Using \textit{Topmetal-${II}^-$} sensors assembled by 0.35 $\mu$m CMOS Integrated Circuit process, this monitor is designed to improve the spatial resolution of detecting radon alpha particles. Concerning small pixel size might has a side effect of worsening energy resolution due to lower signal to noise ratio, a Great4-based simulation is used to figure out energy resolution dependence on pixel size ranging from 60 $\mu$m to 600 $\mu$m. A non-monotonic trend in this region shows a combination effect of pixel size with threshold on pixel, and is analyzed by introducing an empirical expression. Noise on pixel contributes 50 keV Full Width at Half Maximum (FWHM) energy resolution for 400 $\mu$m pixel size at 1 $\sim$ 4 $\sigma$ threshold, which is comparable to the energy resolution caused by energy fluctuation in ionization process of TPC ($\sim$ 20 keV). The total energy resolution after combining both factors is estimated to be 54 keV for 400 $\mu$m pixel size at 1 $\sim$ 4 $\sigma$ threshold. The analysis presented in this paper is helpful to choosing suitable pixel size for future pixelated detectors., Comment: 8 pages, 7 figures